diff --git a/.circleci/config.yml b/.circleci/config.yml
index 4a7d5996..117a01ad 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -9,7 +9,7 @@ jobs:
   deploy-website:
     docker:
       # specify the version you desire here
-      - image: circleci/node:8.11.1
+      - image: cimg/node:17.7.2
 
     steps:
       - checkout
@@ -19,7 +19,7 @@ jobs:
             git config --global user.email "swader@users.noreply.github.com"
             git config --global user.name "Bruno"
             echo "machine github.com login swader password $GITHUB_TOKEN" > ~/.netrc
-            cd website && yarn install && GIT_USER=swader yarn run publish-gh-pages
+            cd website && yarn install && node generateOntology $DIFFBOT_TOKEN && node generateIndustries && GIT_USER=swader yarn run publish-gh-pages
 
 workflows:
   version: 2
diff --git a/docs/api-article.md b/docs/api-article.md
index a4bd7444..06c20d75 100644
--- a/docs/api-article.md
+++ b/docs/api-article.md
@@ -26,12 +26,13 @@ Provide the following arguments:
 | `paging` | Pass `paging=false` to disable automatic concatenation of multiple-page articles. (By default, Diffbot will concatenate up to 20 pages of a single article.) [More on automatic concatenation](guides-multi-page-articles-discussions.md). |
 | `maxTags` | Set the maximum number of automatically-generated tags to return. By default a maximum of ten tags will be returned. |
 | `tagConfidence` | Set the minimum relevance `score` of tags to return, between 0.0 and 1.0. By default only tags with a score equal to or above 0.5 will be returned. |
+| `categoryConfidence` | Set the minimum relevance `score` of categories to return, between 0.5 and 1.0. By default only categories with a score equal to or above 0.5 will be returned. |
 | `discussion` | Pass `discussion=false` to disable automatic extraction of article comments. See [below](#comment-extraction). |
 | `timeout` | Sets a value in milliseconds to wait for the retrieval/fetch of content from the requested URL. The default timeout for the third-party response is 30 seconds (30000). |
 | `callback` | Use for jsonp requests. Needed for cross-domain ajax. |
 | `proxy` | Leave value empty to use default proxies, or specify an IP address of a custom proxy that will be used to fetch the target page, instead of Diffbot's default IPs/proxies. (Ex: `&proxy` or `&proxy=168.212.226.204`) |
 | `proxyAuth` | Used to specify the authentication parameters that will be used with a custom proxy specified in the `&proxy` parameter. (Ex: `&proxyAuth=username:password`) |
-| `naturalLanguage` | Used to request the output of the Diffbot Natural Language API in the field `naturalLanguage`. Example: `&naturalLanguage=entities,facts,categories,sentiment`. |
+| `naturalLanguage` | Used to request the output of the [Diffbot Natural Language API](https://docs.diffbot.com/docs/en/nl-index) in the field `naturalLanguage`. Use this for in-depth analysis of the article text. Example: `&naturalLanguage=entities,facts,categories,sentiment`. |
 
 ### The fields argument
 
@@ -73,15 +74,20 @@ Objects in the Article API's `objects` array will include the following fields:
 | `siteName` | The plain-text name of the site (e.g. `The New York Times` or `Diffbot`). If no site name is automatically determined, the root domain (`diffbot.com`) will be returned. |
 | `publisherRegion` | If known, the region of the article publication. |
 | `publisherCountry` | If known, the country of the article publication. |
+| `location`| Location mentioned at the beginning of the article. |
 | `pageUrl` | URL of submitted page / page from which the article is extracted. |
 | `resolvedPageUrl` | Returned if the `pageUrl` redirects to another URL. |
-| `tags` | Array of tags/entities, generated from analysis of the extracted `text` and cross-referenced with [DBpedia](https://wiki.dbpedia.org/About) and other data sources. Language-specific tags will be returned if the source text is in English, Chinese, French, German, Spanish, Russian, Japanese, Dutch, Polish, Norwegian, Danish or Swedish. |
+| `tags` | Array of tags/entities, generated from analysis of the extracted `title` and `text` fields. Tags are extracted by the [Diffbot Natural Language API](https://docs.diffbot.com/docs/en/nl-index) and linked to the [Diffbot Knowledge Graph](https://www.diffbot.com/products/knowledge-graph/). Tags will be returned if the text is in one of the following languages: English (en), French (fr), Spanish (es), Chinese (zh), German (de), Russian (ru), Japanese (ja), Dutch (nl), Polish (pl), Norwegian (no), Danish (da), Swedish (sv), Italian (it). |
 | ↳`label` | Name of the entity or tag. |
 | ↳`count` | Number of appearances the entity makes within the text content. |
 | ↳`score` | Rating of the entity's relevance to the overall text content (range of 0 to 1) based on various factors. |
 | ↳`rdfTypes` | If the entity can be represented by multiple resources, all of the possible URIs will be returned. |
 | ↳`type` | This legacy field is a simplified precursor to `rdfTypes`, and will return either `organization` or `person` if the entity is either of those types. |
-| ↳`uri` | Link to the primary Diffbot entity for this tag in the [Diffbot Knowledge Graph](https://www.diffbot.com/knowledge-graph/). On older articles, this might be the URI to the entity at DBpedia or another data source, but in most cases it will lead to Diffbot's KG entry which will contain more information about the tag. |
+| ↳`uri` | Link to the primary Diffbot entity for this tag in the [Diffbot Knowledge Graph](https://www.diffbot.com/knowledge-graph/). |
+| `categories` | Array of categories, generated from analysis of the extracted `title` and `text` fields. This field is available for over 100 languages. The complete list of categories can be found at [this link](https://docs.diffbot.com/docs/en/kg-article-categories-list). |
+| ↳`name` | Name of the category. |
+| ↳`score` | Score of how relevant this category is for the article. |
+| ↳`id` | Id of the category. |
 | `images` | Array of images, if present within the article body. |
 | ↳`url` |Fully resolved link to image. If the image `SRC` is encoded as base64 data, the complete data URI will be returned. |
 | ↳`title` | Description or caption of the image. |
diff --git a/docs/api-basics-index.md b/docs/api-basics-index.md
index 8625cf19..b89665e1 100644
--- a/docs/api-basics-index.md
+++ b/docs/api-basics-index.md
@@ -22,6 +22,8 @@ If you know what type of content your URL is, or what to force extraction as a s
 - [Discussion API](api-discussion) is used for extracting threads of content. This can be a review section of a product (indeed, Product API uses the Discussion API internally when extracting comments to include them in the output), a forum or Reddit thread, or a comment section in a blog.
 - [Event API (BETA)](api-event) is used for extracting online and in-person event details for standalone events that occur within a single day. Support for multi-day, multi-track events, i.e. full conferences and festivals, is planned but not yet scheduled.
 
+- [List API (BETA)](api-list) is used for extracting data from any single listings page, such as news index pages, product listings pages, and search engine results pages.
+
 ## Custom API
 
 - [Custom API](api-custom) The Custom API can be used to either correct & augment automatically extracted output or create entirely new custom extractions by defining rules. We have a point-and-click interface that allows you to easily build CSS-based selectors, regular expressions, and attribute filters, or you can also use the Custom API programmatically via..and API.
diff --git a/docs/api-crawlbot-api.md b/docs/api-crawlbot-api.md
index a1464eb9..fa0ffcae 100644
--- a/docs/api-crawlbot-api.md
+++ b/docs/api-crawlbot-api.md
@@ -14,6 +14,8 @@ The Crawlbot API allows you to programmatically manage <a href="https://app.diff
 
 To create a crawl, make a POST request to `https://api.diffbot.com/v3/crawl`.
 
+> Note: The `Content-Type` header should be set to `application/x-www-form-urlencoded`
+
 Provide the following data:
 
 | Argument | Description |
diff --git a/docs/api-intro-list.md b/docs/api-intro-list.md
new file mode 100644
index 00000000..e959a586
--- /dev/null
+++ b/docs/api-intro-list.md
@@ -0,0 +1,24 @@
+---
+id: api-intro-list
+title: List API Introduction
+sidebar_label: Introduction
+description: Introduction of the Diffbot List API
+---
+
+The List API automatically extracts data from any single listings page. Automatically extract pages that contain a primary list of items, such as news index pages, product listings pages, and search engine results pages.
+
+The full API reference of List API can be found [here](api-list).
+
+Learn more about our APIs:
+
+- [Do Diffbot APIs Follow Redirects?](explain-apis-follow-redirects)
+- [Do Diffbot APIs Execute JavaScript?](explain-apis-javascript-support)
+- [How long can a single request take / what is the Diffbot API timeout?](/docs/en/explain-diffbot-api-timeout)
+- [Does Diffbot handle non-English pages?](explain-non-english-pages)
+- [Can I send HTML or text directly to Diffbot APIs?](explain-posting-text-html)
+- [Using Diffbot Proxy Servers / Proxy IPs](explain-using-different-proxies)
+- [What counts as an API call?](explain-what-counts-as-api-call)
+
+Once you've gone through the basics above, proceed with learning about the List API:
+
+- [API reference](api-list)
\ No newline at end of file
diff --git a/docs/api-list.md b/docs/api-list.md
index e6c824c8..a9abed9b 100644
--- a/docs/api-list.md
+++ b/docs/api-list.md
@@ -39,16 +39,16 @@ For example, to return `links` and `meta` (in addition to the default fields), y
 
 ## Response
 
-The Event API returns data in JSON format.
+The List API returns data in JSON format.
 
 Each V3 response includes a `request` object (which returns request-specific metadata), and an `objects` array, which will include the extracted information for all objects on a submitted page.
 
-Objects in the Event API's `objects` array will include the following fields:
+Objects in the List API's `objects` array will include the following fields:
 
 | Field | Description |
 | :---- | :---------- |
-| `type` | Type of object (always `event`). |
-| `pageUrl` | URL of submitted page / page from which the event is extracted. |
+| `type` | Type of object (always `list`). |
+| `pageUrl` | URL of submitted page / page from which the list is extracted. |
 | `resolvedPageUrl` | Returned if the `pageUrl` redirects to another URL. |
 | `title` | Title of the page. |
 | `items` | The primary list of items found on the page. |
@@ -166,7 +166,7 @@ Delivered as a string value as a custom header:
 "X-Forward-X-Evaluate": "function() {start();setTimeout(function(){var loadMoreNode=document.querySelector('a.loadMore');if (loadMoreNode != null) {loadMoreNode.click();setTimeout(function(){end();}, 800);} else {end();}},500);}"
 ```
 
-> Note: X-Evaluate will only be executed if called from the API the rule resides in. If you have an X-Evaluate script in your Article API rule and make a request with the Analyze API that identifies the page as an article, the X-Evaluate will not be executed.
+> Note: X-Evaluate will only be executed if called from the API the rule resides in. If you have an X-Evaluate script in your List API rule and make a request with the Analyze API that identifies the page as a list, the X-Evaluate will not be executed.
 
 ### Saving Data to a Custom Field Using Javascript
 
@@ -191,7 +191,7 @@ function() {
 
 ## Posting Content
 
-If your content is not publicly available (e.g., behind a firewall), you can POST markup directly to the Event API endpoint for analysis:
+If your content is not publicly available (e.g., behind a firewall), you can POST markup directly to the List API endpoint for analysis:
 
 ```plaintext
 https://api.diffbot.com/v3/list?token=...&url=...
@@ -204,5 +204,5 @@ Provide the content to analyze as your POST body, and specify the `Content-Type`
 ### HTML Post Sample
 
 ```plaintext
-curl -H "Content-Type: text/html" -d '<html><head><title>Some List Name</title></head><body><h2>Come join us on February 22nd, 2020</h2><div> at the Chase Center, 1301 2nd Ave, Seattle, WA 98101</div></body></html>' 'https://api.diffbot.com/v3/event?token=...&url=http%3A%2F%2Fstore.diffbot.com'
+curl -H "Content-Type: text/html" -d '<html><head><title>Some List Name</title></head><body><h2>Today's Top News</h2><div> ... </div></body></html>' 'https://api.diffbot.com/v3/list?token=...&url=http%3A%2F%2Fstore.diffbot.com'
 ```
diff --git a/docs/dql-quickstart.md b/docs/dql-quickstart.md
index 91121fe6..7a3f1304 100644
--- a/docs/dql-quickstart.md
+++ b/docs/dql-quickstart.md
@@ -571,7 +571,7 @@ Many new and learning users find Diffbot Query Language and the Knowledge Graph
 
 **_Companies in a City with Female CEO and Specified Size (San Francisco, &lt;500 FTE)_**
 
-`type:Organization location.city.name:"San Francisco" nbEmployeesMax&lt;500 ceo.gender:"Female"`
+`type:Organization location.city.name:"San Francisco" nbEmployeesMax<500 ceo.gender:"Female"`
 
 **_Top Current Employers of Data Science Roles_**
 
@@ -583,11 +583,11 @@ Many new and learning users find Diffbot Query Language and the Knowledge Graph
 
 **_Global Mid-Market Software Companies_**
 
-`type:Organization nbEmployeesMin>100 nbEmployeesMax&lt;1000 industries:"Software Companies" not(industries:"Educational Companies") not(has:parentCompany) not(has:acquiredBy) revSortBy:nbActiveEmployeeEdges`
+`type:Organization nbEmployeesMin>100 nbEmployeesMax<1000 industries:"Software Companies" not(industries:"Educational Companies") not(has:parentCompany) not(has:acquiredBy) revSortBy:nbActiveEmployeeEdges`
 
 **_SMB Advertising Companies With No Investments_**
 
-`type:Organization not(has:investments.amount.value) industries:"Advertising Companies" nbEmployeesMax&lt;=100 nbEmployeesMin>=50`
+`type:Organization not(has:investments.amount.value) industries:"Advertising Companies" nbEmployeesMax<=100 nbEmployeesMin>=50`
 
 **_Individuals Employed In Automotive Software Roles In Europe (&lt;1,100 miles from Hamburg)_**
 
@@ -603,7 +603,7 @@ Many new and learning users find Diffbot Query Language and the Knowledge Graph
 
 **_Small B2B Marketing Agencies Near Atlanta_**
 
-`type:Organization industries:"Service Companies" industries:"Marketing Companies" industries:"Advertising Companies" nbEmployeesMax&lt;=15 location.country.name:"United States" description:"b2b" not(description:or("b2c", "consumer")) near30mi`
+`type:Organization industries:"Service Companies" industries:"Marketing Companies" industries:"Advertising Companies" nbEmployeesMax<=15 location.country.name:"United States" description:"b2b" not(description:or("b2c", "consumer")) near[30mi](name:"Atlanta")`
 
 **_All Whole Foods Locations (By Fact Page Origin)_**
 
@@ -615,26 +615,26 @@ Many new and learning users find Diffbot Query Language and the Knowledge Graph
 
 **_Hires Post a Specific Date at Google_**
 
-`type:Person employments.{employer.name:"Google" from>"2020-01-21" not(from&lt;"2020-01-21")}`
+`type:Person employments.{employer.name:"Google" from>"2020-01-21" not(from<"2020-01-21")}`
 
 **_Industries FAANG Companies Invested In IN 2019_**
 
-`type:Organization investments.{investors.name:or("Facebook","Alphabet","Amazon","Microsoft","Apple","Netflix") date>="01/01/2019" date&lt;="01/01/2020"} facet:industries`
+`type:Organization investments.{investors.name:or("Facebook","Alphabet","Amazon","Microsoft","Apple","Netflix") date>="01/01/2019" date<="01/01/2020"} facet:industries`
 
 
 ### News Monitoring Search Queries
 
 **_Negative Articles About Apple By Week_**
 
-`type:Article tags.{uri:"http://diffbot.com/entity/CHb0_0NEcMwyY8b083taTTw" sentiment&lt;0.0} facet[week]:date`
+`type:Article tags.{uri:"http://diffbot.com/entity/CHb0_0NEcMwyY8b083taTTw" sentiment<0.0} facet[week]:date`
 
 **_Media Mentions of Competitors_**
 
-`type:Article date&lt;30d tags.label:or("Microsoft Teams", "Facebook Workplace”)`
+`type:Article date<30d tags.label:or("Microsoft Teams", "Facebook Workplace")`
 
 **_Most Recirculated Quotes By Joe Biden (Last 30d)_**
 
-`type:Article date&lt;30d quotes.speaker:"Joe Biden" facet:quotes.quote`
+`type:Article date<30d quotes.speaker:"Joe Biden" facet:quotes.quote`
 
 **_Coverage About Protests By Country_**
 
diff --git a/docs/kg-article-categories-list.md b/docs/kg-article-categories-list.md
new file mode 100644
index 00000000..7d5d5ba5
--- /dev/null
+++ b/docs/kg-article-categories-list.md
@@ -0,0 +1,492 @@
+---
+id: kg-article-categories-list
+title: Article Categories
+onPageNav: false
+---
+
+**BETA** — Article categories provide structured context to the topic discussed in a particular piece of text. Unlike [tags](kg-ont-article#tags), categories describe the text as a whole and tend to be more abstract. 
+
+> As of Nov 17, 2021, article categories is in beta and is only supported through [Article Extract](api-intro-article). Ontology and access may be subject to change at any time.
+
+Here's a sample request to extract categories alongside your article extraction —
+
+
+```python
+https://api.diffbot.com/v3/article?token=TOKEN&url=https://blog.diffbot.com/a-less-biased-way-to-discern-media-bias-using-knowledge-graph-enhanced-ai/&naturalLanguage=categories
+```
+
+The category list below outlines all possible categories that may be returned by Diffbot Extract.
+
+| Primary Category    | Secondary Category | Tertiary Category                   |  Quaternary Category |
+| ------------------- | ------------------ | ----------------------------------- | ---- |
+|  Automotive         |                   |   |  |
+|          |  Auto Body Styles                 |  |  |
+|          |                  | Commercial Trucks  |  |
+|          |                  | Convertible  |  |
+|          |                  | Coupe  |  |
+|          |                  | Crossover  |  |
+|          |                  | Hatchback  |  |
+|          |                  | Microcar  |  |
+|          |                  | Minivan  |  |
+|          |                  | Off-Road Vehicles  |  |
+|          |                  | Pickup Trucks  |  |
+|          |                  | SUV  |  |
+|          |                  | Sedan  |  |
+|          |                  | Van  |  |
+|          |  Auto Buying and Selling                 |  |  |
+|          |  Auto Insurance                 |  |  |
+|          |  Auto Parts                 |  |  |
+|          |  Auto Recalls                 |  |  |
+|          |  Auto Rentals                 |  |  |
+|          |  Auto Repair                 |  |  |
+|          |  Auto Safety                 |  |  |
+|          |  Auto Shows                 |  |  |
+|          |  Auto Type                 |  |  |
+|          |                  | Budget Cars  |  |
+|          |                  | Certified Pre-Owned Cars  |  |
+|          |                  | Classic Cars  |  |
+|          |                  | Concept Cars  |  |
+|          |                  | Driverless Cars  |  |
+|          |                  | Green Vehicles  |  |
+|          |                  | Luxury Cars  |  |
+|          |                  | Performance Cars  |  |
+|          |  Car Culture                 |  |  |
+|          |  Motorcycles                 |  |  |
+|          |  Scooters                 |  |  |
+|  Careers         |                   |   |  |
+|          |  Apprenticeships                 |  |  |
+|          |  Career Advice                 |  |  |
+|          |  Career Planning                 |  |  |
+|          |  Job Search                 |  |  |
+|          |  Remote Working                 |  |  |
+|          |  Vocational Training                 |  |  |
+|  Education         |                   |   |  |
+|          |  Adult Education                 |  |  |
+|          |  College Education                 |  |  |
+|          |  Early Childhood Education                 |  |  |
+|          |  Educational Assessment                 |  |  |
+|          |  Homeschooling                 |  |  |
+|          |  Homework and Study                 |  |  |
+|          |  Language Learning                 |  |  |
+|          |  Online Education                 |  |  |
+|          |  Primary Education                 |  |  |
+|          |  Private School                 |  |  |
+|          |  Secondary Education                 |  |  |
+|          |  Special Education                 |  |  |
+|  Events and Attractions         |                   |   |  |
+|          |  Amusement and Theme Parks                 |  |  |
+|          |  Bars &amp; Restaurants                 |  |  |
+|          |  Business Expos &amp; Conferences                 |  |  |
+|          |  Casinos &amp; Gambling                 |  |  |
+|          |  Comedy Events                 |  |  |
+|          |  Concerts &amp; Music Events                 |  |  |
+|          |  Historic Site and Landmark Tours                 |  |  |
+|          |  Museums &amp; Galleries                 |  |  |
+|          |  Musicals                 |  |  |
+|          |  National &amp; Civic Holidays                 |  |  |
+|          |  Nightclubs                 |  |  |
+|          |  Outdoor Activities                 |  |  |
+|          |  Parks &amp; Nature                 |  |  |
+|          |  Party Supplies and Decorations                 |  |  |
+|          |  Personal Celebrations &amp; Life Events                 |  |  |
+|          |                  | Funeral  |  |
+|          |  Zoos &amp; Aquariums                 |  |  |
+|  Family and Relationships         |                   |   |  |
+|          |  Bereavement                 |  |  |
+|          |  Dating                 |  |  |
+|          |  Divorce                 |  |  |
+|          |  Eldercare                 |  |  |
+|          |  Marriage and Civil Unions                 |  |  |
+|          |  Parenting                 |  |  |
+|  Fine Art         |                   |   |  |
+|          |  Digital Arts                 |  |  |
+|          |  Modern Art                 |  |  |
+|          |  Opera                 |  |  |
+|          |  Theater                 |  |  |
+|  Food &amp; Drink         |                   |   |  |
+|          |  Alcoholic Beverages                 |  |  |
+|          |  Barbecues and Grilling                 |  |  |
+|          |  Cooking                 |  |  |
+|          |  Desserts and Baking                 |  |  |
+|          |  Dining Out                 |  |  |
+|          |  Food Allergies                 |  |  |
+|          |  Healthy Cooking and Eating                 |  |  |
+|          |  Non-Alcoholic Beverages                 |  |  |
+|          |  Vegan Diets                 |  |  |
+|          |  Vegetarian Diets                 |  |  |
+|  Healthy Living         |                   |   |  |
+|          |  Children&#39;s Health                 |  |  |
+|          |  Fitness and Exercise                 |  |  |
+|          |  Men&#39;s Health                 |  |  |
+|          |  Nutrition                 |  |  |
+|          |  Senior Health                 |  |  |
+|          |  Weight Loss                 |  |  |
+|          |  Wellness                 |  |  |
+|          |  Women&#39;s Health                 |  |  |
+|  Hobbies &amp; Interests         |                   |   |  |
+|          |  Antiquing and Antiques                 |  |  |
+|          |  Arts and Crafts                 |  |  |
+|          |  Beekeeping                 |  |  |
+|          |  Birdwatching                 |  |  |
+|          |  Cigars                 |  |  |
+|          |  Musical Instruments                 |  |  |
+|          |  Paranormal Phenomena                 |  |  |
+|  Home &amp; Garden         |                   |   |  |
+|          |  Gardening                 |  |  |
+|          |  Home Appliances                 |  |  |
+|          |  Home Improvement                 |  |  |
+|          |  Home Security                 |  |  |
+|          |  Interior Decorating                 |  |  |
+|          |  Landscaping                 |  |  |
+|          |  Outdoor Decorating                 |  |  |
+|          |  Remodeling &amp; Construction                 |  |  |
+|          |  Smart Home                 |  |  |
+|  Medical Health         |                   |   |  |
+|          |  Cosmetic Medical Services                 |  |  |
+|          |  Diseases and Conditions                 |  |  |
+|          |                  | Allergies  |  |
+|          |                  | Blood Disorders  |  |
+|          |                  | Bone and Joint Conditions  |  |
+|          |                  | Brain and Nervous System Disorders  |  |
+|          |                  | Cancer  |  |
+|          |                  | Cold and Flu  |  |
+|          |                  | Dental Health  |  |
+|          |                  | Diabetes  |  |
+|          |                  | Digestive Disorders  |  |
+|          |                  | Ear, Nose and Throat Conditions  |  |
+|          |                  | Endocrine and Metabolic Diseases  |  |
+|          |                  |   | Hormonal Disorders |
+|          |                  |   | Menopause |
+|          |                  |   | Thyroid Disorders |
+|          |                  | Eye and Vision Conditions  |  |
+|          |                  | Foot Health  |  |
+|          |                  | Heart and Cardiovascular Diseases  |  |
+|          |                  | Infectious Diseases  |  |
+|          |                  | Injuries  |  |
+|          |                  |   | First Aid |
+|          |                  | Lung and Respiratory Health  |  |
+|          |                  | Mental Health  |  |
+|          |                  | Reproductive Health  |  |
+|          |                  |   | Birth Control |
+|          |                  |   | Infertility |
+|          |                  |   | Pregnancy |
+|          |                  | Sexual Health  |  |
+|          |                  |   | Sexual Conditions |
+|          |                  | Skin and Dermatology  |  |
+|          |                  | Sleep Disorders  |  |
+|          |                  | Substance Abuse  |  |
+|          |  Medical Tests                 |  |  |
+|          |  Pharmaceutical Drugs                 |  |  |
+|          |  Surgery                 |  |  |
+|          |  Vaccines                 |  |  |
+|  Movies         |                   |   |  |
+|  Music and Audio         |                   |   |  |
+|  News and Politics         |                   |   |  |
+|          |  Crime                 |  |  |
+|          |  Disasters                 |  |  |
+|          |  Law                 |  |  |
+|          |  Local News                 |  |  |
+|          |  Politics                 |  |  |
+|          |                  | Elections  |  |
+|          |                  | Political Issues  |  |
+|          |                  | War and Conflicts  |  |
+|          |  Weather                 |  |  |
+|  Personal Finance         |                   |   |  |
+|          |  Financial Assistance                 |  |  |
+|          |  Financial Planning                 |  |  |
+|          |  Frugal Living                 |  |  |
+|          |  Insurance                 |  |  |
+|          |  Personal Investing                 |  |  |
+|          |  Retirement Planning                 |  |  |
+|  Books and Literature         |                   |   |  |
+|          |  Biographies                 |  |  |
+|          |  Comics and Graphic Novels                 |  |  |
+|          |  Cookbooks                 |  |  |
+|          |  Poetry                 |  |  |
+|  Pets         |                   |   |  |
+|          |  Birds                 |  |  |
+|          |  Cats                 |  |  |
+|          |  Dogs                 |  |  |
+|          |  Pet Adoptions                 |  |  |
+|          |  Pet Supplies                 |  |  |
+|          |  Reptiles                 |  |  |
+|          |  Veterinary Medicine                 |  |  |
+|  Pop Culture         |                   |   |  |
+|          |  Celebrity Deaths                 |  |  |
+|          |  Celebrity Homes                 |  |  |
+|          |  Celebrity Relationships                 |  |  |
+|          |  Celebrity Style                 |  |  |
+|          |  Humor and Satire                 |  |  |
+|  Real Estate         |                   |   |  |
+|  Religion &amp; Spirituality         |                   |   |  |
+|          |  Astrology                 |  |  |
+|          |  Atheism                 |  |  |
+|          |  Buddhism                 |  |  |
+|          |  Christianity                 |  |  |
+|          |  Hinduism                 |  |  |
+|          |  Islam                 |  |  |
+|          |  Judaism                 |  |  |
+|          |  Sikhism                 |  |  |
+|          |  Spirituality                 |  |  |
+|  Science         |                   |   |  |
+|          |  Biological Sciences                 |  |  |
+|          |  Chemistry                 |  |  |
+|          |  Environment                 |  |  |
+|          |  Genetics                 |  |  |
+|          |  Geography                 |  |  |
+|          |  Geology                 |  |  |
+|          |  Physics                 |  |  |
+|          |  Space and Astronomy                 |  |  |
+|  Shopping         |                   |   |  |
+|          |  Coupons and Discounts                 |  |  |
+|          |  Flower Shopping                 |  |  |
+|          |  Gifts and Greetings Cards                 |  |  |
+|          |  Grocery Shopping                 |  |  |
+|          |  Holiday Shopping                 |  |  |
+|          |  Sales and Promotions                 |  |  |
+|  Sports         |                   |   |  |
+|          |  American Football                 |  |  |
+|          |  Australian Rules Football                 |  |  |
+|          |  Auto Racing                 |  |  |
+|          |  Badminton                 |  |  |
+|          |  Baseball                 |  |  |
+|          |  Basketball                 |  |  |
+|          |  Beach Volleyball                 |  |  |
+|          |  Bodybuilding                 |  |  |
+|          |  Bowling                 |  |  |
+|          |  Boxing                 |  |  |
+|          |  Cheerleading                 |  |  |
+|          |  College Sports                 |  |  |
+|          |                  | College Baseball  |  |
+|          |                  | College Basketball  |  |
+|          |                  | College Football  |  |
+|          |  Cricket                 |  |  |
+|          |  Cycling                 |  |  |
+|          |  Darts                 |  |  |
+|          |  Disabled Sports                 |  |  |
+|          |  Diving                 |  |  |
+|          |  Extreme Sports                 |  |  |
+|          |                  | Canoeing and Kayaking  |  |
+|          |                  | Climbing  |  |
+|          |                  | Paintball  |  |
+|          |                  | Scuba Diving  |  |
+|          |                  | Skateboarding  |  |
+|          |                  | Snowboarding  |  |
+|          |                  | Surfing and Bodyboarding  |  |
+|          |  Fantasy Sports                 |  |  |
+|          |  Field Hockey                 |  |  |
+|          |  Figure Skating                 |  |  |
+|          |  Fishing Sports                 |  |  |
+|          |  Golf                 |  |  |
+|          |  Gymnastics                 |  |  |
+|          |  Horse Racing                 |  |  |
+|          |  Ice Hockey                 |  |  |
+|          |  Lacrosse                 |  |  |
+|          |  Martial Arts                 |  |  |
+|          |  Olympic Sports                 |  |  |
+|          |                  | Summer Olympic Sports  |  |
+|          |                  | Winter Olympic Sports  |  |
+|          |  Poker and Professional Gambling                 |  |  |
+|          |  Rodeo                 |  |  |
+|          |  Rowing                 |  |  |
+|          |  Rugby                 |  |  |
+|          |  Sailing                 |  |  |
+|          |  Skiing                 |  |  |
+|          |  Snooker&#x2F;Pool&#x2F;Billiards                 |  |  |
+|          |  Soccer                 |  |  |
+|          |  Softball                 |  |  |
+|          |  Sports Equipment                 |  |  |
+|          |  Swimming                 |  |  |
+|          |  Table Tennis                 |  |  |
+|          |  Tennis                 |  |  |
+|          |  Track and Field                 |  |  |
+|          |  Volleyball                 |  |  |
+|          |  Walking                 |  |  |
+|          |  Water Polo                 |  |  |
+|          |  Weightlifting                 |  |  |
+|          |  Wrestling                 |  |  |
+|  Business and Finance         |                   |   |  |
+|          |  Business                 |  |  |
+|          |                  | Awards  |  |
+|          |                  | Business Accounting &amp; Finance  |  |
+|          |                  | Business Administration  |  |
+|          |                  | Business Banking &amp; Finance  |  |
+|          |                  |   | Acquisitions, Mergers and Takeovers |
+|          |                  |   | Angel Investment |
+|          |                  |   | Bankruptcy |
+|          |                  |   | Business Loans |
+|          |                  |   | Debt Factoring &amp; Invoice Discounting |
+|          |                  |   | Private Equity |
+|          |                  |   | Sale &amp; Lease Back |
+|          |                  |   | Venture Capital |
+|          |                  | Business I.T.  |  |
+|          |                  | Business Operations  |  |
+|          |                  | Business Utilities  |  |
+|          |                  | Consumer Issues  |  |
+|          |                  |   | Recalls |
+|          |                  | Contracts and Agreements  |  |
+|          |                  | Environmental, Social and Governance (ESG)  |  |
+|          |                  | Executive Leadership &amp; Management  |  |
+|          |                  | Funding  |  |
+|          |                  | Government Business  |  |
+|          |                  | Green Solutions  |  |
+|          |                  | Human Resources  |  |
+|          |                  | Intellectual Property  |  |
+|          |                  | Large Business  |  |
+|          |                  | Litigation  |  |
+|          |                  | Logistics  |  |
+|          |                  | Marketing and Advertising  |  |
+|          |                  | Partnerships and Joint Ventures  |  |
+|          |                  | Personnel Changes  |  |
+|          |                  |   | Key Hires |
+|          |                  |   | Layoffs |
+|          |                  | Products and Services Announcements  |  |
+|          |                  | Real Estate Transactions  |  |
+|          |                  | Regulatory Approvals  |  |
+|          |                  |   | Investigational New Drug Application |
+|          |                  | Sales  |  |
+|          |                  | Small and Medium-sized Business  |  |
+|          |                  | Startups  |  |
+|          |                  | Stock Offerings and IPOs  |  |
+|          |                  | Stock Price News  |  |
+|          |                  |   | Dividends |
+|          |                  |   | Investment Opinion |
+|          |                  |   | Sales and Earnings |
+|          |                  |   | Stock Split |
+|          |  Economy                 |  |  |
+|          |                  | Commodities  |  |
+|          |                  | Currencies  |  |
+|          |                  | Financial Crisis  |  |
+|          |                  | Financial Reform  |  |
+|          |                  | Financial Regulation  |  |
+|          |                  | Gasoline Prices  |  |
+|          |                  | Housing Market  |  |
+|          |                  | Interest Rates  |  |
+|          |                  | Job Market  |  |
+|          |  Industries                 |  |  |
+|          |                  | Advertising Industry  |  |
+|          |                  | Agriculture  |  |
+|          |                  | Apparel Industry  |  |
+|          |                  | Automotive Industry  |  |
+|          |                  | Aviation Industry  |  |
+|          |                  | Biotech and Biomedical Industry  |  |
+|          |                  | Civil Engineering Industry  |  |
+|          |                  | Construction Industry  |  |
+|          |                  | Defense Industry  |  |
+|          |                  | Education industry  |  |
+|          |                  | Entertainment Industry  |  |
+|          |                  | Environmental Services Industry  |  |
+|          |                  | Financial Industry  |  |
+|          |                  | Food Industry  |  |
+|          |                  | Healthcare Industry  |  |
+|          |                  | Hospitality Industry  |  |
+|          |                  | Information Services Industry  |  |
+|          |                  | Legal Services Industry  |  |
+|          |                  | Logistics and Transportation Industry  |  |
+|          |                  | Management Consulting Industry  |  |
+|          |                  | Manufacturing Industry  |  |
+|          |                  | Mechanical and Industrial Engineering Industry  |  |
+|          |                  | Media Industry  |  |
+|          |                  | Metals Industry  |  |
+|          |                  | Non-Profit Organizations  |  |
+|          |                  | Pharmaceutical Industry  |  |
+|          |                  | Power and Energy Industry  |  |
+|          |                  | Publishing Industry  |  |
+|          |                  | Real Estate Industry  |  |
+|          |                  | Retail Industry  |  |
+|          |                  | Technology Industry  |  |
+|          |                  | Telecommunications Industry  |  |
+|  Style &amp; Fashion         |                   |   |  |
+|          |  Beauty                 |  |  |
+|          |  Body Art                 |  |  |
+|          |  Fashion Trends                 |  |  |
+|          |  Men&#39;s Fashion                 |  |  |
+|          |  Women&#39;s Fashion                 |  |  |
+|  Technology &amp; Computing         |                   |   |  |
+|          |  Artificial Intelligence                 |  |  |
+|          |  Augmented Reality                 |  |  |
+|          |  Computing                 |  |  |
+|          |                  | Computer Networking  |  |
+|          |                  | Computer Peripherals  |  |
+|          |                  | Computer Software and Applications  |  |
+|          |                  |   | 3-D Graphics |
+|          |                  |   | Antivirus Software |
+|          |                  |   | Browsers |
+|          |                  |   | Computer Animation |
+|          |                  |   | Databases |
+|          |                  |   | Desktop Publishing |
+|          |                  |   | Digital Audio |
+|          |                  |   | Graphics Software |
+|          |                  |   | Operating Systems |
+|          |                  |   | Photo Editing Software |
+|          |                  |   | Shareware and Freeware |
+|          |                  |   | Video Software |
+|          |                  |   | Web Conferencing |
+|          |                  | Data Storage and Warehousing  |  |
+|          |                  | Desktops  |  |
+|          |                  | Information and Network Security  |  |
+|          |                  | Internet  |  |
+|          |                  |   | Cloud Computing |
+|          |                  |   | Email |
+|          |                  |   | IT and Internet Support |
+|          |                  |   | Internet for Beginners |
+|          |                  |   | Internet of Things |
+|          |                  |   | Search |
+|          |                  |   | Social Networking |
+|          |                  |   | Web Design and HTML |
+|          |                  |   | Web Development |
+|          |                  |   | Web Hosting |
+|          |                  | Laptops  |  |
+|          |                  | Programming Languages  |  |
+|          |                  | Technical Documentation  |  |
+|          |  Consumer Electronics                 |  |  |
+|          |                  | Cameras and Camcorders  |  |
+|          |                  | Home Entertainment Systems  |  |
+|          |                  | Smartphones  |  |
+|          |                  | Tablets and E-readers  |  |
+|          |                  | Wearable Technology  |  |
+|          |  Robotics                 |  |  |
+|          |  Virtual Reality                 |  |  |
+|  Television         |                   |   |  |
+|  Travel         |                   |   |  |
+|          |  Travel Locations                 |  |  |
+|          |                  | Africa Travel  |  |
+|          |                  | Asia Travel  |  |
+|          |                  | Australia and Oceania Travel  |  |
+|          |                  | Europe Travel  |  |
+|          |                  | North America Travel  |  |
+|          |                  | Polar Travel  |  |
+|          |                  | South America Travel  |  |
+|          |  Travel Preparation and Advice                 |  |  |
+|          |  Travel Type                 |  |  |
+|          |                  | Adventure Travel  |  |
+|          |                  | Air Travel  |  |
+|          |                  | Beach Travel  |  |
+|          |                  | Budget Travel  |  |
+|          |                  | Business Travel  |  |
+|          |                  | Camping  |  |
+|          |                  | Cruises  |  |
+|          |                  | Day Trips  |  |
+|          |                  | Family Travel  |  |
+|          |                  | Honeymoons and Getaways  |  |
+|          |                  | Hotels and Motels  |  |
+|          |                  | Rail Travel  |  |
+|          |                  | Road Trips  |  |
+|          |                  | Spas  |  |
+|  Video Gaming         |                   |   |  |
+|          |  Console Games                 |  |  |
+|          |  Mobile Games                 |  |  |
+|          |  PC Games                 |  |  |
+|          |  eSports                 |  |  |
+
+
+<style>
+/* Hides the Right-Hand Secondary Nav for a Full Width Industry Table */
+.onPageNav {
+    display: none;
+}
+/* Hides the Unnecessary Prev/Next Buttons for this Reference Doc */
+.docs-prevnext {
+    display: none;
+}
+</style>
\ No newline at end of file
diff --git a/docs/kg-employment-categories-list.md b/docs/kg-employment-categories-list.md
index 7836a38f..c25555fb 100644
--- a/docs/kg-employment-categories-list.md
+++ b/docs/kg-employment-categories-list.md
@@ -2,6 +2,7 @@
 id: kg-employment-categories-list
 title: Employment Categories
 onPageNav: false
+generatedBy: generateIndustries.js
 ---
 
 Employment categories (see [employments ontology reference](kg-ont-person#employments)) are canonicalized Domains, Seniority, and/or Roles inferred from a given person's employment title and description. Employment categories are only applicable for the [Person data type](kg-ont-person).
@@ -33,8 +34,19 @@ An employment category reflecting various career types (e.g. *Human Resources*,
 | Domain          |  Business         |                   |   |  |  |
 | Domain          |  Construction, Electricity, Plumbing         |                   |   |  |  |
 | Domain          |  Counseling, Social Work, Person Care         |                   |   |  |  |
+|                     |          |  Academic Administration                 |  |  |  |
 | Domain          |  Design and Graphic Arts         |                   |   |  |  |
 | Domain          |  Engineering, IT and Software Development         |                   |   |  |  |
+|                     |          |  Artificial Intelligence                 |  |  |  |
+|                     |          |  Backend Developer                 |  |  |  |
+|                     |          |  Cybersecurity                 |  |  |  |
+|                     |          |  Data Science                 |  |  |  |
+|                     |          |  DevOps Developer                 |  |  |  |
+|                     |          |  Frontend Developer                 |  |  |  |
+|                     |          |  Fullstack Developer or Architect                 |  |  |  |
+|                     |          |  Games Developer                 |  |  |  |
+|                     |          |  Information Technology                 |  |  |  |
+|                     |          |  Mobile Developer                 |  |  |  |
 | Domain          |  Finance         |                   |   |  |  |
 | Domain          |  Food Preparation and Service         |                   |   |  |  |
 | Domain          |  Healthcare and Medicine         |                   |   |  |  |
@@ -71,6 +83,7 @@ An employment category indicating a person's relative rank (e.g. *Junior*, or *S
 |                     |          |                  | Leadership  |  |  |
 |                     |          |                  |   | Chief Officer |  |
 |                     |          |                  |   |  | CAO |
+|                     |          |                  |   |  | CBO |
 |                     |          |                  |   |  | CCO |
 |                     |          |                  |   |  | CEO |
 |                     |          |                  |   |  | CFO |
@@ -82,6 +95,8 @@ An employment category indicating a person's relative rank (e.g. *Junior*, or *S
 |                     |          |                  |   | President |  |
 |                     |          |                  |   | Vice President |  |
 |                     |          |                  | Shareholder  |  |  |
+|                     |          |  Head of government                 |  |  |  |
+|                     |          |  Head of state                 |  |  |  |
 |                     |          |  Manager                 |  |  |  |
 
 ## By Seniority
diff --git a/docs/kg-enhance-quickstart.md b/docs/kg-enhance-quickstart.md
new file mode 100644
index 00000000..f5f65f26
--- /dev/null
+++ b/docs/kg-enhance-quickstart.md
@@ -0,0 +1,99 @@
+---
+id: kg-enhance-quickstart
+title: Enhance Quick Start
+sidebar_label: Enhance Quick Start
+---
+This guide is meant to provide techniques for using Diffbot's Enhance (data enrichment) product using our visual interface. For API access, see our [Enhance API Reference](/enhance).
+
+## Enriching Organization or Person Data In The Interface
+From the home screen of the [Diffbot dashboard](https://app.diffbot.com) users may find our data enrichment offering in the sidebar or main content area listed as Enhance. 
+
+Once you've arrived at the manual Enhance interface, users may select whether they would like to enrich a person or organization. 
+
+![Enhance Page](/img/enhance-get-started/enhance-one.PNG)
+
+At least one input field is required, and the greater the number of fields provided the higher likelihood that data will be successfully enriched. 
+
+![Additional Options](/img/enhance-get-started/enhance-two.PNG)
+After toggling additional options, users may alter several settings. These include: 
+
+- **Toggling refresh mode** - refresh mode recrawls the origin pages for all facts associated with an entity refreshing data. 
+- **Toggling search mode** - search mode searches across our web crawl data to seek out and merge in new facts that are not presently attached to the entity in question. 
+- **Altering the match threshhold** - by default entities must match the input to be enriched by a threshold of .29 or above on a 0-1 scale. Lower the threshold to lower match criteria or raise the threshold to perform the inverse. 
+- **Specifying the number of matches** - By default our enrichment seeks to match input with a single entity. Raise the match number to return multiple of the top-matching results. Within the visual interface multiple results will be shown in a results page. 
+
+**Note:** Refresh and search mode increase credit usage compared to default setting Enhance jobs.
+
+After executing an Enhance job, results may be clicked through to see visual Knowledge Graph entity pages. Additionally, results may be exported via JSON or CSV in the upper right corner of the results page. 
+
+![Export Enhance Via CSV](/img/enhance-get-started/enhance-three.PNG)
+
+While JSON export results will return all default fields, CSV export allows users to choose from a range of fields to export. A preview of results allows you to select which fields you would like and alter column names. 
+
+The "for multi-value fields, select all the value" toggle specifies whether you want the latest entry or all entries for multi-value fields. An example of this could be a list of employers for a person data enrichment. 
+
+## Enriching In Bulk Using Bulk Enhance
+
+Typically you will have more than one entity you will want to manually enrich. A new bulk Enhance job can be started in the left sidebar under Enhance in the [Knowledge Graph Interface](https://app.diffbot.com).
+
+First, name your bulk Enhance job so that you can return to it once it is completed. Completed or in-progress bulk Enhance jobs as well as a range of statistics about records processed, remaining time, and match rate can be viewed in the [All bulk Enhance Jobs](https://app.diffbot.com/enhance/bulk/) tab of the interface. 
+
+Next you'll have the choice of uploading a csv or manually inputting the entities to enrich. For manual input, you'll need to follow the standard column order if supplying multiple fields. When supplying name input alone, commas may be skipped in input.  
+
+**Standard Bulk Enhance Column Order:**
+`Name, Location, Description, URL`
+
+For CSV upload, you can provide custom ordered columns utilizing the same column names above or utilize our standard template. 
+
+After toggling additional options, users may alter several settings. These include: 
+
+- **Toggling refresh mode** - refresh mode recrawls the origin pages for all facts associated with an entity refreshing data. 
+- **Toggling search mode** - search mode searches across our web crawl data to seek out and merge in new facts that are not presently attached to the entity in question. 
+- **Altering the match threshhold** - by default entities must match the input to be enriched by a threshold of .32 or above on a 0-1 scale. Lower the threshold to lower match criteria or raise the threshold to perform the inverse. 
+- **Specifying the number of matches** - By default our enrichment seeks to match input with a single entity. Raise the match number to return multiple of the top-matching results. Within the visual interface multiple results will be shown in a results page. 
+
+**Note:** Refresh and search mode increase credit usage compared to default setting Enhance jobs.
+![Bulk Enhance Job Started](/img/enhance-get-started/enhance-four.PNG)
+Upon executing your bulk Enhance job, your job will enter the queue. During this time and throughout the execution of your enrichment you may check in on the status of your crawl including match rates and estimated time until completion in the overview, results, and stats tabs. Additionally you may leave the page and find a view of your ongoing or completed bulk Enhances in the sidebar under Enhance labelled "All Bulk Enhance Jobs." 
+
+You can export your results in the "All Bulk Enhance Jobs" tab in JSON or CSV. 
+
+![Export Enhance Via CSV](/img/enhance-get-started/enhance-three.PNG)
+
+While JSON export results will return all default fields, CSV export allows users to choose from a range of fields to export. A preview of results allows you to select which fields you would like and alter column names. 
+
+The "for multi-value fields, select all the value" toggle specifies whether you want the latest entry or all entries for multi-value fields. An example of this could be a list of employers for a person data enrichment. 
+
+
+
+## Enriching A Spreadsheet Using Integrations
+One benefit of utilizing Diffbot's Google Sheets or Excel integrations for CSV enrichment is that you can inject data directly into your working sheet. 
+![Installing Diffbot For Sheets](/img/enhance-get-started/install-g-sheets.gif)
+Enriching data using **Diffbot's Google Sheets Add-On** involves first installing the add-on, then logging in with your API token which can be found in the top right corner of the home screen of the [Knowledge Graph Interface](https://app.diffbot.com). 
+![Enriching in Google Sheets](/img/enhance-get-started/g-sheets-function.gif)
+Enrichment utilizes two Google Sheets functions. `=ENHANCE_ORGANIZATION` and `=ENHANCE_PERSON`.
+
+For organizations, the following fields may be passed to the function.
+
+- `field` - The field of an organization entity to return. Multiple fields may be supplied separated by commas. For a full list of fields attached to organizations, see our [organization ontology page](/docs/en/kg-ont-organization).
+- `name` (optional) - a provided name for an organization.
+- `url` (optional) - a provided homepage for the organization. 
+- `location` (optional) - a provided location for the organization. 
+- `description` (optional) - a provided description of what the organization does.  
+
+For person enrichment the following fields may be passed to the function.
+
+- `field` - The field of an organization entity to return. Multiple fields may be supplied separated by commas. For a full list of fields attached to organizations, see our [organization ontology page](/docs/en/kg-ont-person).
+- `name` (optional) - a provided name for an organization.
+- `email` (optional) - a provided email for the organization. 
+- `employer` (optional) - a provided employer for the organization. 
+- `location` (optional) - a provided location for the organization. 
+- `description` (optional) - a provided description of what the organization does.  
+
+**Tip:** for the field input, use absolute references to column header cells so you can apply your function to many cells at once by dragging (shown in prior GIF). 
+
+Enriching data using **Diffbot's Excel Add-On** provides a way to feed your existing spreadsheet of organizations or people through a visual interface where you can map your input and choose which fields to output. 
+
+Check out our [Diffbot Excel Add-In docs](/docs/en/dql-excel#enhance-an-organization-profile-with-sample-data) for more information on using Enhance in docs, or watch our walkthrough video below. 
+
+<iframe width="560" height="315" src="https://www.youtube.com/embed/lbG5fl5foD8" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
\ No newline at end of file
diff --git a/docs/kg-index.md b/docs/kg-index.md
index 2dff5d01..f4483805 100644
--- a/docs/kg-index.md
+++ b/docs/kg-index.md
@@ -16,6 +16,8 @@ This page is a directory of KG and Enhance related content.
 
 - [Accessing the Knowledge Graph](kg-accessing) - access the knowledge graph through the UI or the API
 - [API Clients](kg-clients) - use the API through your favorite programming language
+- [Knowledge Graph Quick Start](/docs/en/dql-quickstart) spend a few hours gaining mastery of Diffbot's Knowledge Graph and Diffbot Query Language
+- [Enhance Quick Start](/docs/en/kg-enhance-quickstart) - use our visual interface to Enrich data using Diffbot Enhance
 - [Microsoft Excel DQL Plugin](dql-excel) - use the power of DQL in your spreadsheets and enhance your data
 - [Google Sheets Add-on](kg-gsheets) - like the Excel plugin, but in Google Sheets
 
diff --git a/docs/kg-industry-list.md b/docs/kg-industry-list.md
index e57e92ec..6e796137 100644
--- a/docs/kg-industry-list.md
+++ b/docs/kg-industry-list.md
@@ -2,358 +2,888 @@
 id: kg-industry-list
 title: Organization Industries
 onPageNav: false
+generatedBy: generateIndustries.js
 ---
 
-This reference is helpful for narrowing down queries for organizations on the [Diffbot Knowledge Graph](dql-quickstart) by [industry](kg-ont-organization#industries). Diffbot Knowledge Graph Search supports querying by industry names or NAICS codes. Feel free to use either.
+> 📘 Organization Industries is getting better
+> 
+> This reference now contains the new taxonomy for industries v2, which contains over 250% more categories than the [previous industries taxonomy](<>) .
+> 
+> Legacy organization industries will be deprecated **Friday, August 30, 2024**.
+> 
+> Please see the [migration guide](<>)  for a complete overview of the changes.
+
+This reference is helpful for narrowing down queries for organizations on the [Diffbot Knowledge Graph](dql-quickstart) by [industry category](ont-organization#categories). Diffbot Knowledge Graph Search supports querying by category names, NAICS, or SIC codes. Feel free to use any of them.
 
 An example [DQL](dql-index) query using an industry on this list might look like this —
 
 ```
-type:Organization industries:"Medical Associations"
+type:Organization categories:"Software Companies"
 ```
 
-| Primary Industry    | Secondary Industry | Tertiary Industry | NAICS                   |
-| ------------------- | ------------------ | ----------------- | ----------------------- |
-| Agricultural Organizations          |                    |                   | 110000 |
-|                     | Animal Farms         |                   | 112900 |
-|                     | Apiculture Organizations         |                   | 112910 |
-|                     | Fruits And Vegetables         |                   | 111200 |
-|                     | Oilseed And Grain Farming         |                   | 111100 |
-|                     | Pet Breeders         |                   | 115210 |
-|                     | Poultry Farms         |                   | 112300 |
-| Associations And Societies          |                    |                   | 813920 |
-|                     | Construction Associations         |                   | 813920 |
-|                     | Educational Associations         |                   | 813920 |
-|                     | Engineering Societies         |                   | 813920 |
-|                     | Financial Associations         |                   | 813910 |
-|                     | Journalism Associations         |                   | 813920 |
-|                     | Law Associations         |                   | 813920 |
-|                     | Library Associations         |                   | 813920 |
-|                     | Medical Associations         |                   | 813212 |
-|                     | Social Sciences Organizations         |                   | 813410 |
-|                     | Standards Organizations         |                   |  |
-|                     | Youth Organizations         |                   |  |
-| Chemical Companies          |                    |                   | 325000 |
-|                     | Fertilizer Companies         |                   | 325320 |
-|                     | Paint Manufacturers         |                   | 325510 |
-|                     | Petrochemical Companies         |                   | 325110 |
-| Clothing Companies          |                    |                   | 315200 |
-|                     | High Fashion Brands         |                   |  |
-|                     | Shoe Brands         |                   | 316200 |
-|                     | Sportswear Brands         |                   | 339920 |
-|                     | Underwear Brands         |                   |  |
-| Community Services          |                    |                   |  |
-|                     | Cultural Services         |                   |  |
-|                     |                    | Art Galleries        | 712110 |
-|                     |                    | Libraries        | 519120 |
-|                     |                    | Museums        | 712110 |
-|                     |                    | Theatres        | 711310 |
-|                     | Recreation Services         |                   |  |
-|                     |                    | Amusement Parks        | 713110 |
-|                     |                    | Bowling Centers        | 713950 |
-|                     |                    | Casinos        | 713210 |
-|                     |                    | Cinemas And Movie Theaters        | 512131 |
-|                     |                    | Fitness And Sports Centers        | 713940 |
-|                     |                    | Golf Courses And Country Clubs        | 713910 |
-|                     |                    | National Parks        | 712190 |
-|                     |                    | Stadiums And Arenas        |  |
-|                     |                    | Zoos And Aquaria        | 712130 |
-| Construction Companies          |                    |                   | 236000 |
-|                     | Construction Associations         |                   | 813920 |
-|                     | Electrical Contractors         |                   | 238210 |
-|                     | Flooring Contractors         |                   | 238330 |
-|                     | General Contractors         |                   | 238000 |
-|                     | Heating And Air Conditioning Contractors         |                   | 238220 |
-|                     | Painting Contractors         |                   | 238320 |
-|                     | Plumbing Contractors         |                   | 238220 |
-|                     | Remodeling And Restoration Contractors         |                   | 236118 |
-|                     | Residential Building Constructors         |                   | 236100 |
-|                     | Roofing Contractors         |                   | 238160 |
-| Consumer Service Companies          |                    |                   | 561000 |
-|                     | Barber Shops         |                   | 812111 |
-|                     | Beauty Salons And Spa         |                   | 812112 |
-|                     | Car Washes         |                   | 811192 |
-|                     | Cleaning Companies         |                   | 561720 |
-|                     | Counseling Organizations         |                   | 624190 |
-|                     | Coworking Spaces         |                   |  |
-|                     | Death Care Services         |                   | 812210 |
-|                     | Locksmith Services         |                   | 561622 |
-|                     | Moving And Storage Companies         |                   | 484210 |
-|                     | Pest Control Services         |                   | 561710 |
-|                     | Photographic Studios         |                   | 541921 |
-|                     | Recruiting And Employment Agencies         |                   | 561311 |
-|                     | Repair And Maintenance         |                   | 811000 |
-|                     |                    | Appliance Repair and Maintenance        | 811412 |
-|                     |                    | Computer Repair Services        | 811212 |
-|                     |                    | Vehicle Repair And Maintenance        | 811111 |
-|                     | Ridesharing And Taxi Companies         |                   | 485310 |
-|                     | Security Companies         |                   | 561612 |
-|                     | Shopping Delivery Services         |                   | 492100 |
-|                     | Tattoo Shops         |                   | 812199 |
-|                     | Tourism Agencies         |                   | 561510 |
-|                     | Vehicle Rental Companies         |                   | 532111 |
-|                     | Veterinary Organizations         |                   | 541940 |
-| Design Companies          |                    |                   | 541400 |
-|                     | Architecture Firms         |                   | 541310 |
-|                     | Graphic Design Companies         |                   | 541430 |
-|                     | Industrial Design Firms         |                   | 541420 |
-|                     | Packaging Companies         |                   | 561910 |
-|                     | Photographic Studios         |                   | 541921 |
-| Educational Organizations          |                    |                   | 611000 |
-|                     | Educational Associations         |                   | 813920 |
-|                     | Educational Institutions         |                   | 611000 |
-|                     |                    | Academies        | 611310 |
-|                     |                    | Research Institutes And Labs        | 611310 |
-|                     |                    | Schools        | 611110 |
-|                     |                    | Universities And Colleges        | 611310 |
-|                     | Online Learning Companies         |                   |  |
-| Energy Companies          |                    |                   | 221000 |
-|                     | Natural Gas Companies         |                   | 221200 |
-|                     | Nuclear Energy Companies         |                   | 221113 |
-|                     | Renewable Energy Companies         |                   | 221100 |
-|                     |                    | Hydroelectric Power Companies        | 221111 |
-|                     |                    | Solar Energy Companies        | 221114 |
-|                     |                    | Wind Energy Companies        | 221115 |
-| Entertainment Companies          |                    |                   | 710000 |
-|                     | Gambling Companies         |                   | 713290 |
-|                     | Performing Arts Companies         |                   | 711100 |
-|                     |                    | Dance Groups        | 711120 |
-|                     |                    | Musical Groups        | 711130 |
-|                     | Sports Clubs         |                   | 711211 |
-| Environmental Organizations          |                    |                   | 813312 |
-|                     | Climate Change Organizations         |                   | 813312 |
-|                     | Nature Conservation Organizations         |                   | 813312 |
-|                     | Waste Organizations And Recycling Facilities         |                   | 221320 |
-|                     | Water Organizations         |                   | 221310 |
-| Financial Services Companies          |                    |                   | 520000 |
-|                     | Banks         |                   | 522110 |
-|                     | Brokerage Firms         |                   | 523120 |
-|                     | Digital Currencies Companies         |                   |  |
-|                     | Financial Associations         |                   | 813910 |
-|                     | Financial Data Vendors         |                   |  |
-|                     | Financial Technology Companies         |                   |  |
-|                     | Insurance Companies         |                   | 524100 |
-|                     |                    | Health Insurance Companies        | 524114 |
-|                     |                    | Life Insurance Companies        | 524113 |
-|                     |                    | Property insurance Companies        | 524126 |
-|                     | Investment Companies         |                   | 523999 |
-|                     | Management Consulting Firms         |                   | 541611 |
-|                     | Mortgage Lenders         |                   | 522310 |
-|                     | Payment Service Providers         |                   | 522320 |
-|                     | Stock Exchanges         |                   | 523210 |
-| Food And Drink Companies          |                    |                   | 311000 |
-|                     | Animal Food Manufacturers         |                   | 311100 |
-|                     | Drink Companies         |                   | 312100 |
-|                     |                    | Bottled Water Companies        | 312112 |
-|                     |                    | Breweries        | 312120 |
-|                     |                    | Coffee Companies        | 311920 |
-|                     |                    | Distilleries        | 312140 |
-|                     |                    | Soft Drinks Manufacturers        | 312111 |
-|                     |                    | Tea Companies        | 311920 |
-|                     |                    | Wineries        | 312130 |
-|                     | Food Companies         |                   | 311000 |
-| Hospitality Companies          |                    |                   | 720000 |
-|                     | Bars         |                   | 722410 |
-|                     | Cafes         |                   | 722515 |
-|                     | Fast Food Restaurants         |                   | 722513 |
-|                     | Restaurants         |                   | 722500 |
-|                     | Tourist Accommodations         |                   | 721199 |
-|                     |                    | Campgrounds        | 721211 |
-|                     |                    | Hostels And Motels        | 721110 |
-|                     |                    | Hotels        | 721110 |
-|                     |                    | Resorts        | 721199 |
-| Infrastructure          |                    |                   |  |
-|                     | Airports Services         |                   |  |
-|                     | Bridges         |                   |  |
-|                     | Ports         |                   |  |
-|                     | Railway Stations         |                   |  |
-| Manufacturing Companies          |                    |                   | 330000 |
-|                     | Building Materials Companies         |                   | 327120 |
-|                     |                    | Cement Companies        | 327300 |
-|                     |                    | Ceramics Manufacturers        | 327110 |
-|                     |                    | Glassmaking Companies        | 327200 |
-|                     |                    | Metal Companies        | 332300 |
-|                     | Electrical Equipment Manufacturers         |                   | 335300 |
-|                     | Electronic Products Manufacturers         |                   | 335000 |
-|                     |                    | Audio Video Equipment Manufacturers        | 334310 |
-|                     |                    | Display Technology Companies        | 334419 |
-|                     |                    | Mobile Phone Manufacturers        | 334220 |
-|                     |                    | Watch Manufacturing Companies        | 334518 |
-|                     | Engine Manufacturers         |                   | 336310 |
-|                     | Furniture Manufacturers         |                   | 337100 |
-|                     | Home Appliance Manufacturers         |                   | 335220 |
-|                     |                    | Air Conditioning Companies        | 333400 |
-|                     | Machine Manufacturers         |                   | 333100 |
-|                     |                    | Agricultural Machinery Manufacturers        | 333111 |
-|                     |                    | Construction Equipment Manufacturers        | 333120 |
-|                     |                    | Turbine Manufacturers        | 333600 |
-|                     | Medical Technology Companies         |                   | 325400 |
-|                     | Miscellaneous Manufacturers         |                   | 330000 |
-|                     |                    | Eyewear Manufacturers        | 339115 |
-|                     |                    | Jewelry Manufacturers        | 339910 |
-|                     |                    | Knife Manufacturing        | 332215 |
-|                     |                    | Luggage Manufacturers        | 316991 |
-|                     |                    | Pen Manufacturers        | 339940 |
-|                     | Optics Manufacturing Companies         |                   | 333314 |
-|                     | Pulp And Paper Companies         |                   | 322100 |
-|                     | Semiconductor Companies         |                   | 334400 |
-|                     | Soap And Cosmetics Companies         |                   | 325620 |
-|                     | Sporting Goods Manufacturers         |                   | 339920 |
-|                     | Textile Mills Manufacturers         |                   | 313310 |
-|                     | Tobacco Companies         |                   | 312230 |
-|                     | Tool Manufacturers         |                   | 333517 |
-|                     | Toy Manufacturers         |                   | 339930 |
-|                     | Vehicle Parts Manufacturers         |                   | 336390 |
-| Media And Information Companies          |                    |                   | 510000 |
-|                     | Broadcasting Companies         |                   | 515100 |
-|                     |                    | Radio Stations        | 515112 |
-|                     |                    | Television Broadcasting Companies        | 515120 |
-|                     |                    | Television Channels        |  |
-|                     | Motion Picture Companies         |                   | 512100 |
-|                     |                    | Animation Studios        | 512110 |
-|                     |                    | Film Companies        | 512110 |
-|                     | Music Companies         |                   | 512250 |
-|                     | Publishing Companies         |                   | 511100 |
-|                     |                    | Book Publishing Companies        | 511130 |
-|                     |                    | Magazine Publishing Companies        | 511120 |
-|                     |                    | Newspaper Companies        | 511110 |
-|                     | Telecommunications Companies         |                   | 517312 |
-|                     | Video Game Companies         |                   | 511210 |
-| Medical Organizations          |                    |                   | 620000 |
-|                     | Alternative Medicine Organizations         |                   | 621399 |
-|                     | Biotechnology Companies         |                   | 541714 |
-|                     | Dental Companies         |                   | 621210 |
-|                     | Health Care Companies         |                   | 623000 |
-|                     | Home Health Care         |                   | 621610 |
-|                     | Hospitals         |                   | 622110 |
-|                     | Medical Associations         |                   | 813212 |
-|                     | Medical Laboratories         |                   | 621511 |
-|                     | Mental Health Organizations         |                   | 621330 |
-|                     | Optometrists         |                   | 621320 |
-|                     | Pharmacies         |                   | 446110 |
-|                     | Physiotherapy Organization         |                   | 621340 |
-|                     | Public Health Organizations         |                   | 621491 |
-|                     | Veterinary Organizations         |                   | 541940 |
-| Mining Companies          |                    |                   | 210000 |
-|                     | Coal Mining Companies         |                   | 212100 |
-|                     | Metal Mining Companies         |                   | 212200 |
-|                     | Oil Companies         |                   | 211120 |
-| Motor Vehicle Manufacturers          |                    |                   | 336100 |
-|                     | Aircraft Manufacturers         |                   | 336411 |
-|                     | Autonomous Vehicles         |                   |  |
-|                     | Bus Manufacturers         |                   | 336120 |
-|                     | Car Manufacturers         |                   | 336111 |
-|                     | Cycle Manufacturers         |                   | 336991 |
-|                     | Electric Vehicles         |                   | 336320 |
-|                     | Luxury Motor Vehicle Manufacturers         |                   | 336111 |
-|                     | Motorcycle Manufacturers         |                   | 336991 |
-|                     | Shipbuilding Companies         |                   | 336611 |
-|                     | Truck Manufacturers         |                   | 336120 |
-| Pharmaceutical Companies          |                    |                   | 325412 |
-| Professional Service Companies          |                    |                   | 541000 |
-|                     | Accounting Services         |                   | 541200 |
-|                     | Advertising Companies         |                   | 541810 |
-|                     | Business Incubators         |                   | 523999 |
-|                     | Defense Companies         |                   | 971100 |
-|                     | Engineering Consulting Firms         |                   | 541330 |
-|                     | Event Management Companies         |                   |  |
-|                     | Law Firms         |                   | 541110 |
-|                     | Marketing Companies         |                   | 541613 |
-|                     | Polling Companies         |                   | 541910 |
-|                     | Postal Organizations         |                   | 491110 |
-|                     | Real Estate Companies         |                   | 531210 |
-|                     | Translation Services         |                   | 541930 |
-|                     | Veterinary Organizations         |                   | 541940 |
-| Public Administration          |                    |                   | 920000 |
-|                     | Courts         |                   | 922110 |
-|                     | Embassies And Consulates         |                   | 928120 |
-|                     | Federal Agencies         |                   | 922190 |
-|                     | Fire Departments         |                   | 922160 |
-|                     | Government Departments         |                   |  |
-|                     | Intergovernmental Organizations         |                   | 928120 |
-|                     | International Organizations         |                   | 928120 |
-|                     | Local Governments         |                   | 921110 |
-|                     | Military Bases         |                   | 928110 |
-|                     | Military Related Organizations         |                   | 928110 |
-|                     | Ministries         |                   | 921110 |
-|                     | Police Departments         |                   | 922120 |
-|                     | Political Parties         |                   | 813940 |
-| Religious Organizations          |                    |                   | 813110 |
-| Retailers          |                    |                   | 440000 |
-|                     | Auction Houses         |                   | 453998 |
-|                     | Automotive Part Retailers         |                   | 441310 |
-|                     | Bookstores         |                   | 451211 |
-|                     | Building Materials Retailers         |                   | 444190 |
-|                     |                    | Floor Covering Stores        | 442210 |
-|                     |                    | Hardware Stores        | 444130 |
-|                     |                    | Plumbing Equipment And Supplies        | 423720 |
-|                     | Clothing Retailers         |                   | 448100 |
-|                     |                    | Children Clothing Retailers        | 448130 |
-|                     |                    | Eyewear Retailers        | 446130 |
-|                     |                    | Footwear Retailers        | 448200 |
-|                     |                    | Lingerie Retailers        | 448190 |
-|                     |                    | Sporting Goods Retailers        | 451110 |
-|                     | Consumer Electronics Retailers         |                   | 443142 |
-|                     | Florist Companies         |                   | 424930 |
-|                     | Food Retailers         |                   | 445000 |
-|                     |                    | Convenience Stores        | 445120 |
-|                     |                    | Food Markets        | 445200 |
-|                     |                    | Liquor Stores        | 445310 |
-|                     |                    | Supermarkets        | 445110 |
-|                     | Furniture Retailers         |                   | 442110 |
-|                     | Gas Station         |                   | 447190 |
-|                     | Jewelry Retailers         |                   | 448310 |
-|                     | Luxury Brands         |                   |  |
-|                     | Music Retailers         |                   | 451140 |
-|                     | Online Retailers         |                   |  |
-|                     | Pet Shops         |                   | 453910 |
-|                     | Pharmacies         |                   | 446110 |
-|                     | Photographic Equipment And Supplies         |                   | 423410 |
-|                     | Superstores         |                   | 452311 |
-|                     | Toy And Video Game Retailers         |                   | 451120 |
-|                     | Vehicle Retailers And Dealership         |                   | 441100 |
-| Software Companies          |                    |                   | 511210 |
-|                     | Artificial Intelligence Companies         |                   | 541511 |
-|                     |                    | Computer Vision Companies        | 541511 |
-|                     |                    | Natural Language Processing Companies        | 541511 |
-|                     |                    | Robotics Companies        | 541511 |
-|                     |                    | Virtual Reality Companies        | 541511 |
-|                     | Bioinformatics Organizations         |                   | 541511 |
-|                     | Computer Hardware Companies         |                   | 334000 |
-|                     |                    | Cloud Computing Providers        | 518210 |
-|                     |                    | Computer Storage Companies        | 334112 |
-|                     |                    | Internet Of Things Companies        | 541511 |
-|                     |                    | Networking Companies        | 334118 |
-|                     | Data Analytics Companies         |                   | 518210 |
-|                     | Data Providers         |                   | 518210 |
-|                     | Enterprise Software Companies         |                   | 511210 |
-|                     |                    | Business Software Companies        | 541511 |
-|                     |                    | CRM Software Companies        | 541511 |
-|                     |                    | Database Companies        | 541511 |
-|                     |                    | Security Software Companies        | 541511 |
-|                     | Open Source Software Organizations         |                   | 541511 |
-|                     | Social Networking Companies         |                   | 541511 |
-|                     | Software As A Service Companies         |                   | 511210 |
-|                     | Software Consulting Firms         |                   | 541618 |
-|                     | Video Game Companies         |                   | 511210 |
-|                     | Video Messaging Companies         |                   | 511210 |
-|                     | Web Design Companies         |                   | 541511 |
-| Transport Companies          |                    |                   | 480000 |
-|                     | Airlines         |                   | 481111 |
-|                     | Cruise Lines         |                   | 483112 |
-|                     | Freight And Logistics Companies         |                   | 541614 |
-|                     | Public Transport Operators         |                   | 485100 |
-|                     | Railway Companies         |                   | 482100 |
-|                     | Ridesharing And Taxi Companies         |                   | 485310 |
-|                     | Vehicle Rental Companies         |                   | 532111 |
 
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+| L1 Category    | L2 Category | L3 Category | L4 Category | L5 Category | NAICS                   | SIC                   |
+| ------------------- | ------------------ | ----------------- | ----------------- | ----------------- | ----------------------- | --------------------- |
+| Aerospace And Defense Companies          |                    |                   |                   |                   | 336400 | 3700 |
+|                     | Aircraft Manufacturers         |                   |                   |                   | 336411 | 3721 |
+|                     | Aircraft Parts Manufacturers         |                   |                   |                   | 336413 | 3724 |
+|                     | Defense Companies         |                   |                   |                   | 928110 | 9711 |
+|                     |                    | Defense Electronic Companies        |                   |                   | 928110 | 9711 |
+|                     |                    | Weapons Manufacturers        |                   |                   | 928110 | 3480 |
+|                     | Military Vehicles Manufacturers         |                   |                   |                   | 336400 | 3700 |
+|                     | Space And Satellite Manufacturers         |                   |                   |                   | 336400 | 3760 |
+|                     | Unmanned Aerial System Companies         |                   |                   |                   | 336400 | 3700 |
+| Agricultural Organizations          |                    |                   |                   |                   | 110000 | 0200 |
+|                     | Animal Farms         |                   |                   |                   | 112900 | 0290 |
+|                     | Apiculture Organizations         |                   |                   |                   | 112910 | 0279 |
+|                     | Fruits And Vegetables         |                   |                   |                   | 111200 | 0161 |
+|                     | Oilseed And Grain Farming         |                   |                   |                   | 111100 | 0190 |
+|                     | Poultry Farms         |                   |                   |                   | 112300 | 0259 |
+| Associations And Societies          |                    |                   |                   |                   | 813920 | 8690 |
+|                     | Communities         |                   |                   |                   | 813920 | 8690 |
+|                     | Construction Associations         |                   |                   |                   | 813920 | 8620 |
+|                     | Educational Associations         |                   |                   |                   | 813920 | 8620 |
+|                     | Engineering Societies         |                   |                   |                   | 813920 | 8620 |
+|                     | Financial Associations         |                   |                   |                   | 813910 | 8620 |
+|                     | Journalism Associations         |                   |                   |                   | 813920 | 8620 |
+|                     | Law Associations         |                   |                   |                   | 813920 | 8620 |
+|                     | Library Associations         |                   |                   |                   | 813920 | 8620 |
+|                     | Social Sciences Organizations         |                   |                   |                   | 813410 | 8641 |
+|                     | Standards Organizations         |                   |                   |                   | 813920 | 8620 |
+|                     | Youth Organizations         |                   |                   |                   | 813410 | 8641 |
+| Basic Materials Companies          |                    |                   |                   |                   |  |  |
+|                     | Cement Companies         |                   |                   |                   | 327300 | 2891 |
+|                     | Ceramics Manufacturers         |                   |                   |                   | 327110 | 1450 |
+|                     | Chemical Companies         |                   |                   |                   | 325000 | 2899 |
+|                     |                    | Fertilizer Companies        |                   |                   | 325320 | 2879 |
+|                     |                    | Paint Manufacturers        |                   |                   | 325510 | 2850 |
+|                     |                    | Plastic Producers        |                   |                   | 325000 | 2899 |
+|                     | Glassmaking Companies         |                   |                   |                   | 327210 | 1793 |
+|                     | Mining Companies         |                   |                   |                   | 210000 | 1000 |
+|                     | Petrochemical Companies         |                   |                   |                   | 325110 | 2869 |
+|                     | Pulp And Paper Companies         |                   |                   |                   | 322100 | 5110 |
+|                     | Textile Mills Manufacturers         |                   |                   |                   | 313310 | 2200 |
+| Community Services          |                    |                   |                   |                   | 713000 | 7900 |
+|                     | Amusement Parks         |                   |                   |                   | 713110 | 7996 |
+|                     | Art Galleries         |                   |                   |                   | 712110 | 8412 |
+|                     | Bowling Centers         |                   |                   |                   | 713950 | 7933 |
+|                     | Cinemas And Movie Theaters         |                   |                   |                   | 512131 | 7832 |
+|                     | Cultural Centers         |                   |                   |                   | 713000 | 7900 |
+|                     | Fitness And Sports Centers         |                   |                   |                   | 713940 | 7991 |
+|                     | Golf Courses And Country Clubs         |                   |                   |                   | 713910 | 7997 |
+|                     | Libraries         |                   |                   |                   | 519210 | 8231 |
+|                     | Museums         |                   |                   |                   | 712110 | 8412 |
+|                     | Parks And Recreation Area         |                   |                   |                   | 713000 | 7900 |
+|                     | Recreational Camps         |                   |                   |                   | 721214 | 7032 |
+|                     | Ski Resort         |                   |                   |                   | 713920 | 7999 |
+|                     | Stadiums And Arenas         |                   |                   |                   | 711310 | 7941 |
+|                     | Theatres         |                   |                   |                   | 711310 | 7832 |
+|                     | Zoos And Aquaria         |                   |                   |                   | 712130 | 8422 |
+| Construction Companies          |                    |                   |                   |                   | 236000 | 1629 |
+|                     | Electrical Contractors         |                   |                   |                   | 238210 | 1730 |
+|                     | Flooring Contractors         |                   |                   |                   | 238330 | 1752 |
+|                     | General Contractors         |                   |                   |                   | 238000 | 1500 |
+|                     | Heating And Air Conditioning Contractors         |                   |                   |                   | 238220 | 1710 |
+|                     | Infrastructure Construction Companies         |                   |                   |                   | 237990 | 1600 |
+|                     | Landscaping Services         |                   |                   |                   | 561730 | 0782 |
+|                     | Painting Contractors         |                   |                   |                   | 238320 | 1790 |
+|                     | Plumbing Contractors         |                   |                   |                   | 238220 | 1790 |
+|                     | Power Plants Construction Companies         |                   |                   |                   | 237130 | 1629 |
+|                     | Recreational Facilities Construction Companies         |                   |                   |                   | 237990 | 1629 |
+|                     | Remodeling And Restoration Contractors         |                   |                   |                   | 236118 | 1500 |
+|                     | Residential Building Constructors         |                   |                   |                   | 236110 | 1520 |
+|                     | Roofing Contractors         |                   |                   |                   | 238160 | 1790 |
+| Consumer Products          |                    |                   |                   |                   | 339999 | 3999 |
+|                     | Apparel And Accessories Companies         |                   |                   |                   | 315990 | 2300 |
+|                     |                    | Clothing Companies        |                   |                   | 315200 | 2389 |
+|                     |                    | Eyewear Manufacturers        |                   |                   | 339115 | 3827 |
+|                     |                    | Jewelry Manufacturers        |                   |                   | 339910 | 3911 |
+|                     |                    | Luggage Manufacturers        |                   |                   | 316990 | 3161 |
+|                     |                    | Pen Manufacturers        |                   |                   | 339940 | 3951 |
+|                     |                    | Shoe Brands        |                   |                   | 316210 | 5139 |
+|                     |                    | Sportswear Brands        |                   |                   | 339920 | 3949 |
+|                     |                    | Underwear Brands        |                   |                   | 315120 | 2389 |
+|                     |                    | Watch Manufacturing Companies        |                   |                   | 334519 | 3870 |
+|                     | Appliance Manufacturers         |                   |                   |                   | 335210 | 3630 |
+|                     |                    | Air Conditioning Companies        |                   |                   | 333410 | 1710 |
+|                     |                    | Knife Manufacturing        |                   |                   | 332215 | 3911 |
+|                     | Beauty Care Companies         |                   |                   |                   | 339999 | 3999 |
+|                     | Beverage Companies         |                   |                   |                   | 312100 | 2080 |
+|                     |                    | Bottled Water Companies        |                   |                   | 312112 | 2086 |
+|                     |                    | Breweries        |                   |                   | 312120 | 2082 |
+|                     |                    | Coffee Companies        |                   |                   | 311920 | 2095 |
+|                     |                    | Distilleries        |                   |                   | 312140 | 2085 |
+|                     |                    | Soft Drinks Companies        |                   |                   | 312111 | 2086 |
+|                     |                    | Tea Companies        |                   |                   | 311920 | 2095 |
+|                     |                    | Wineries        |                   |                   | 312130 | 2084 |
+|                     | Food Companies         |                   |                   |                   | 311000 | 2000 |
+|                     |                    | Cocoa Companies        |                   |                   | 311351 | 2066 |
+|                     |                    | Dairy Companies        |                   |                   | 311000 | 2000 |
+|                     | Furniture Manufacturers         |                   |                   |                   | 337100 | 5021 |
+|                     | Music Instruments Manufacturers         |                   |                   |                   | 339992 | 3931 |
+|                     | Pet Care Companies         |                   |                   |                   | 339999 | 3999 |
+|                     |                    | Animal Food Manufacturers        |                   |                   | 311110 | 2048 |
+|                     | Sporting Goods Manufacturers         |                   |                   |                   | 339920 | 3949 |
+|                     |                    | Cycle Manufacturers        |                   |                   | 336991 | 3900 |
+|                     | Toys Companies         |                   |                   |                   | 339930 | 3944 |
+| Consumer Services          |                    |                   |                   |                   | 810000 | 7200 |
+|                     | Barber Shops         |                   |                   |                   | 812111 | 7241 |
+|                     | Beauty Salons And Spa         |                   |                   |                   | 812112 | 7231 |
+|                     | Car Washes         |                   |                   |                   | 811192 | 7542 |
+|                     | Catering Services         |                   |                   |                   | 722320 | 5812 |
+|                     | Cleaning Companies         |                   |                   |                   | 561720 | 7349 |
+|                     | Coworking Spaces         |                   |                   |                   | 531120 | 7389 |
+|                     | Death Care Services         |                   |                   |                   | 812210 | 7261 |
+|                     | Food Delivery Services         |                   |                   |                   | 722513 | 5963 |
+|                     | Laundry Companies         |                   |                   |                   | 812320 | 3582 |
+|                     | Locksmith Services         |                   |                   |                   | 561622 | 7699 |
+|                     | Parking Services         |                   |                   |                   | 812930 | 7521 |
+|                     | Pest Control Services         |                   |                   |                   | 561710 | 7342 |
+|                     | Pet Breeders         |                   |                   |                   | 115210 | 0752 |
+|                     | Repair And Maintenance         |                   |                   |                   | 811000 | 7600 |
+|                     |                    | Appliance Repair Services        |                   |                   | 811412 | 7629 |
+|                     |                    | Computer Repair Services        |                   |                   | 811210 | 7378 |
+|                     |                    | Vehicle Repair Services        |                   |                   | 811111 | 7530 |
+|                     |                    | Wellness Facility Maintenance Services        |                   |                   | 561790 | 7349 |
+|                     | Restricted Services         |                   |                   |                   | 810000 | 7200 |
+|                     |                    | Adult Entertainment Clubs        |                   |                   | 722410 | 5813 |
+|                     |                    | Cannabis Companies        |                   |                   | 459991 | 7200 |
+|                     |                    | Casinos        |                   |                   | 713210 | 7999 |
+|                     |                    | Firearms Retailers        |                   |                   | 459110 | 5091 |
+|                     |                    | Gambling Companies        |                   |                   | 713290 | 7999 |
+|                     |                    | Liquor Stores        |                   |                   | 445320 | 5920 |
+|                     |                    | Tobacco Companies        |                   |                   | 312230 | 5194 |
+|                     |                    | Tobacco Stores        |                   |                   | 459991 | 5993 |
+|                     | Shopping Delivery Services         |                   |                   |                   | 492100 | 7389 |
+|                     | Tattoo Shops         |                   |                   |                   | 812199 | 7299 |
+|                     | Tourism Agencies         |                   |                   |                   | 561510 | 4724 |
+| Educational Organizations          |                    |                   |                   |                   | 611000 | 8290 |
+|                     | Educational Institutions         |                   |                   |                   | 611000 | 8290 |
+|                     |                    | Academies        |                   |                   | 611310 | 8221 |
+|                     |                    | K12 Schools        |                   |                   | 611110 | 8211 |
+|                     |                    |                   | Pre Schools        |                   | 611110 | 8211 |
+|                     |                    |                   | Primary Schools        |                   | 611110 | 8211 |
+|                     |                    |                   | Secondary Schools        |                   | 611110 | 8211 |
+|                     |                    | Universities And Colleges        |                   |                   | 611310 | 8221 |
+|                     |                    |                   | Online University        |                   | 611310 | 8221 |
+|                     | Research Institutes         |                   |                   |                   | 611000 | 8732 |
+|                     | Sports Schools         |                   |                   |                   | 611620 | 8290 |
+| Energy Companies          |                    |                   |                   |                   | 221000 | 1382 |
+|                     | Coal Mining Companies         |                   |                   |                   | 212100 | 1200 |
+|                     | Nuclear Energy Companies         |                   |                   |                   | 221113 | 4911 |
+|                     | Oil And Gas Companies         |                   |                   |                   | 221000 | 1382 |
+|                     |                    | Oil And Gas Drilling        |                   |                   | 213111 | 1381 |
+|                     |                    | Oil And Gas Exploration And Production        |                   |                   | 211120 | 1311 |
+|                     |                    | Oil And Gas Refining And Marketing        |                   |                   | 221000 | 1382 |
+|                     |                    | Oil And Gas Storage And Transportation        |                   |                   | 221000 | 1382 |
+|                     | Renewable Energy Companies         |                   |                   |                   | 221100 | 4911 |
+|                     |                    | Biomass Energy Companies        |                   |                   | 221100 | 4911 |
+|                     |                    | Geothermal Energy Companies        |                   |                   | 221116 | 4911 |
+|                     |                    | Hydroelectric Power Companies        |                   |                   | 221111 | 4911 |
+|                     |                    | Renewable Fuels Companies        |                   |                   | 221100 | 4911 |
+|                     |                    | Solar Energy Companies        |                   |                   | 221114 | 4911 |
+|                     |                    | Wind Energy Companies        |                   |                   | 221115 | 4911 |
+|                     | Thermal Power Generation Companies         |                   |                   |                   | 221000 | 1382 |
+| Environmental Organizations          |                    |                   |                   |                   | 813312 | 8399 |
+|                     | Climate Change Organizations         |                   |                   |                   | 813312 | 8399 |
+|                     | Nature Conservation Organizations         |                   |                   |                   | 813312 | 8399 |
+| Financial Services Companies          |                    |                   |                   |                   | 520000 | 6000 |
+|                     | Banking Services         |                   |                   |                   | 522110 | 6021 |
+|                     |                    | Banks        |                   |                   | 522110 | 6020 |
+|                     |                    |                   | Central Banks        |                   | 521100 | 6011 |
+|                     |                    | Credit Unions        |                   |                   | 522130 | 6061 |
+|                     | Currency And Lending Services         |                   |                   |                   | 520000 | 6000 |
+|                     |                    | Currency Exchange Services        |                   |                   | 522390 | 6099 |
+|                     |                    | Money Transfer And Remittance Services        |                   |                   | 522320 | 6099 |
+|                     |                    | Mortgage And Loans Lenders        |                   |                   | 522310 | 6162 |
+|                     | Financial Research Companies         |                   |                   |                   | 520000 | 6000 |
+|                     |                    | Credit Rating and Reporting Services        |                   |                   | 561450 | 7323 |
+|                     |                    | ESG Research        |                   |                   | 520000 | 6000 |
+|                     |                    | Financial Data Vendors        |                   |                   | 520000 | 6282 |
+|                     |                    | Investment Research Services        |                   |                   | 520000 | 6000 |
+|                     |                    | Regulatory and Compliance Research        |                   |                   | 520000 | 6000 |
+|                     | Insurance Companies         |                   |                   |                   | 524100 | 6300 |
+|                     |                    | Health Insurance Companies        |                   |                   | 524114 | 6321 |
+|                     |                    | Life Insurance Companies        |                   |                   | 524113 | 6310 |
+|                     |                    | Property Insurance Companies        |                   |                   | 524126 | 6390 |
+|                     | Investment Companies         |                   |                   |                   | 523999 | 6722 |
+|                     |                    | Asset Management Services        |                   |                   | 523940 | 6282 |
+|                     |                    | Brokerage Firms        |                   |                   | 523150 | 6211 |
+|                     |                    | Business Incubators        |                   |                   | 523999 | 7300 |
+|                     |                    | Investment Management Companies        |                   |                   | 525000 | 6722 |
+|                     |                    |                   | Hedge Funds        |                   | 525000 | 6799 |
+|                     |                    |                   | Pension Funds        |                   | 525110 | 6371 |
+|                     |                    |                   | Private Equity Firms        |                   | 523940 | 6799 |
+|                     |                    |                   | Venture Capital Firms        |                   | 523910 | 6799 |
+|                     |                    | Stock Exchanges        |                   |                   | 523210 | 6231 |
+|                     |                    | Wealth Management Services        |                   |                   | 523940 | 6282 |
+|                     | Payment Services Providers         |                   |                   |                   | 522320 | 6099 |
+|                     |                    | B2B Payment Services        |                   |                   | 522320 | 6099 |
+|                     |                    | Credit and Debit Card Payment Processing        |                   |                   | 522320 | 6099 |
+|                     |                    | Payment Cards Providers        |                   |                   | 522320 | 6099 |
+|                     |                    |                   | Credit Card Providers        |                   | 522210 | 6099 |
+|                     |                    |                   | Fuel Card Providers        |                   | 522320 | 6099 |
+|                     |                    |                   | Prepaid Card Providers        |                   | 522320 | 6099 |
+|                     |                    | Payment Technology Solutions        |                   |                   | 522320 | 6099 |
+|                     |                    |                   | Digital Payment Gateways        |                   | 522320 | 6099 |
+|                     |                    |                   | Digital Wallet Services        |                   | 522320 | 6099 |
+|                     |                    |                   | Installment Payment And BNPL Services        |                   | 522291 | 6099 |
+|                     |                    |                   | Mobile Payment Services        |                   | 522320 | 6099 |
+|                     |                    |                   | Peer-to-Peer Payment Services        |                   | 522320 | 6099 |
+|                     |                    |                   | Point-of-Sale Services        |                   | 541519 | 6099 |
+| Hospitality Companies          |                    |                   |                   |                   | 720000 | 7000 |
+|                     | Food And Drink Companies         |                   |                   |                   | 311000 | 2000 |
+|                     |                    | Bars        |                   |                   | 722410 | 5813 |
+|                     |                    | Cafes        |                   |                   | 722515 | 5810 |
+|                     |                    | Fast Food Restaurants        |                   |                   | 722513 | 5812 |
+|                     |                    | Restaurants        |                   |                   | 722500 | 5812 |
+|                     | Tourist Accommodations         |                   |                   |                   | 721100 | 7000 |
+|                     |                    | Campgrounds        |                   |                   | 721211 | 7033 |
+|                     |                    | Cruise Lines        |                   |                   | 483112 | 4481 |
+|                     |                    | Hostels And Motels        |                   |                   | 721110 | 7011 |
+|                     |                    | Hotels        |                   |                   | 721110 | 7011 |
+|                     |                    | Resorts        |                   |                   | 721199 | 7011 |
+| Manufacturing Companies          |                    |                   |                   |                   | 330000 | 3900 |
+|                     | Agricultural Machinery Manufacturers         |                   |                   |                   | 333111 | 3500 |
+|                     | Construction Equipment Manufacturers         |                   |                   |                   | 333120 | 3523 |
+|                     | Construction Supplies Manufacturers         |                   |                   |                   | 330000 | 3900 |
+|                     | Electrical Components Manufacturers         |                   |                   |                   | 335000 | 3900 |
+|                     |                    | Batteries Manufacturers        |                   |                   | 335910 | 3900 |
+|                     | Electronic Components Manufacturers         |                   |                   |                   | 334400 | 3900 |
+|                     | Energy Equipment Manufacturers         |                   |                   |                   | 333100 | 3530 |
+|                     |                    | Oil And Gas Equipment Manufacturers        |                   |                   | 333132 | 3533 |
+|                     |                    | Photovoltaics Manufacturers        |                   |                   | 333100 | 3530 |
+|                     |                    | Wind Turbine Manufacturers        |                   |                   | 333611 | 3530 |
+|                     | Engine Manufacturers         |                   |                   |                   | 336310 | 3510 |
+|                     | Industrial Machinery Manufacturers         |                   |                   |                   | 333200 | 3500 |
+|                     | Medical Equipment Manufacturers         |                   |                   |                   | 339112 | 3841 |
+|                     | Motor Vehicle Manufacturers         |                   |                   |                   | 336100 | 3711 |
+|                     |                    | Bus Manufacturers        |                   |                   | 336120 | 3711 |
+|                     |                    | Car Manufacturers        |                   |                   | 336110 | 3711 |
+|                     |                    | Electric Vehicles        |                   |                   | 336320 | 5012 |
+|                     |                    | Motorcycle Manufacturers        |                   |                   | 336991 | 3750 |
+|                     |                    | Shipbuilding Companies        |                   |                   | 336611 | 3731 |
+|                     |                    | Truck Manufacturers        |                   |                   | 336120 | 3711 |
+|                     | Packaging Manufacturers         |                   |                   |                   | 330000 | 3900 |
+|                     | Self-Service Machine Manufacturers         |                   |                   |                   | 330000 | 3900 |
+|                     | Tool Manufacturers         |                   |                   |                   | 333517 | 3900 |
+|                     | Vehicle Parts Manufacturers         |                   |                   |                   | 336390 | 3714 |
+|                     |                    | Tires Manufacturers        |                   |                   | 326211 | 3011 |
+| Media And Information Companies          |                    |                   |                   |                   | 510000 | 2700 |
+|                     | Broadcasting Companies         |                   |                   |                   | 516100 | 4830 |
+|                     |                    | Radio Stations        |                   |                   | 516110 | 4832 |
+|                     |                    | Television Broadcasting Companies        |                   |                   | 516120 | 4833 |
+|                     |                    |                   | Television News Networks        |                   | 516120 | 4833 |
+|                     | Digital Publishing Companies         |                   |                   |                   | 510000 | 2700 |
+|                     |                    | Financial News Publishers        |                   |                   | 510000 | 7383 |
+|                     |                    | News Agencies        |                   |                   | 516210 | 7383 |
+|                     |                    | News Aggregators Publishers        |                   |                   | 510000 | 2700 |
+|                     |                    | Online News Publishers        |                   |                   | 513110 | 2711 |
+|                     |                    | Price Comparison Platform        |                   |                   | 510000 | 2700 |
+|                     |                    | Reviews Platform        |                   |                   | 510000 | 2700 |
+|                     | Digital Streaming Companies         |                   |                   |                   | 510000 | 2700 |
+|                     |                    | Music Streaming Services        |                   |                   | 510000 | 2700 |
+|                     |                    | Podcast Hosting Platforms        |                   |                   | 510000 | 2700 |
+|                     |                    | Video Streaming Services        |                   |                   | 510000 | 2700 |
+|                     | Entertainment Production Companies         |                   |                   |                   | 510000 | 2700 |
+|                     |                    | Animation Studios        |                   |                   | 512110 | 7812 |
+|                     |                    | Film Companies        |                   |                   | 512110 | 7812 |
+|                     |                    | Music Companies        |                   |                   | 512250 | 7929 |
+|                     | Publishing Companies         |                   |                   |                   | 513100 | 2740 |
+|                     |                    | Book Publishing Companies        |                   |                   | 513130 | 2731 |
+|                     |                    | Comics Publishing Companies        |                   |                   | 513100 | 2740 |
+|                     |                    | Education Publishing Company        |                   |                   | 513100 | 2740 |
+|                     |                    | Magazine Publishing Companies        |                   |                   | 513120 | 2740 |
+|                     |                    | Newspaper Publishing Companies        |                   |                   | 513110 | 2711 |
+|                     |                    | Science Publishing Companies        |                   |                   | 513100 | 2740 |
+| Medical Organizations          |                    |                   |                   |                   | 620000 | 8049 |
+|                     | Alternative Medicine Organizations         |                   |                   |                   | 621399 | 8049 |
+|                     | Biotechnology Companies         |                   |                   |                   | 541714 | 8731 |
+|                     | Counseling Organizations         |                   |                   |                   | 624190 | 8322 |
+|                     | Dental Companies         |                   |                   |                   | 621210 | 8021 |
+|                     | Health Care Companies         |                   |                   |                   | 623000 | 8049 |
+|                     | Home Health Care         |                   |                   |                   | 621610 | 8082 |
+|                     | Hospitals         |                   |                   |                   | 622110 | 8060 |
+|                     | Medical Associations         |                   |                   |                   | 813212 | 8620 |
+|                     | Medical Laboratories         |                   |                   |                   | 621511 | 8071 |
+|                     | Mental Health Organizations         |                   |                   |                   | 621330 | 8049 |
+|                     | Optometrists         |                   |                   |                   | 621320 | 8042 |
+|                     | Pharmaceutical Companies         |                   |                   |                   | 325412 | 2834 |
+|                     | Physiotherapy Organization         |                   |                   |                   | 621340 | 8049 |
+|                     | Public Health Organizations         |                   |                   |                   | 621491 | 8011 |
+|                     | Veterinary Organizations         |                   |                   |                   | 541940 | 0740 |
+| Performing Arts Companies          |                    |                   |                   |                   | 711100 | 7922 |
+|                     | Dance Groups         |                   |                   |                   | 711120 | 7922 |
+|                     | Musical Groups         |                   |                   |                   | 711130 | 7929 |
+|                     | Theatre Companies         |                   |                   |                   | 711110 | 7922 |
+| Professional Service Companies          |                    |                   |                   |                   | 541000 | 7300 |
+|                     | Airports Services         |                   |                   |                   | 541000 | 4580 |
+|                     | Architectural Services         |                   |                   |                   | 541310 | 8712 |
+|                     |                    | Architecture Firms        |                   |                   | 541310 | 8712 |
+|                     |                    | Interior Design Services        |                   |                   | 541410 | 8712 |
+|                     | Business Services         |                   |                   |                   | 541000 | 7300 |
+|                     |                    | Benefits Consulting Services        |                   |                   | 541000 | 7300 |
+|                     |                    | Corporate Training Services        |                   |                   | 541000 | 7300 |
+|                     |                    | Management Consulting Services        |                   |                   | 541610 | 8742 |
+|                     |                    | Payroll Services        |                   |                   | 541214 | 8721 |
+|                     |                    | Sales Consulting Services        |                   |                   | 541000 | 7300 |
+|                     | Energy Management Services         |                   |                   |                   | 541620 | 7300 |
+|                     | Engineering Consulting Firms         |                   |                   |                   | 541330 | 8748 |
+|                     | Event Management Services         |                   |                   |                   | 561920 | 7300 |
+|                     | Finance Services         |                   |                   |                   | 541000 | 7300 |
+|                     |                    | Accounting Services        |                   |                   | 541200 | 8720 |
+|                     |                    | Auditing Services        |                   |                   | 541200 | 8721 |
+|                     |                    | Bookkeeping Services        |                   |                   | 541200 | 8721 |
+|                     |                    | Financial Consulting Services        |                   |                   | 523000 | 6799 |
+|                     |                    | Tax Services        |                   |                   | 541213 | 7291 |
+|                     | Graphic Design Services         |                   |                   |                   | 541430 | 7336 |
+|                     | Legal Services         |                   |                   |                   | 541110 | 8111 |
+|                     | Logistics Services         |                   |                   |                   | 488510 | 4731 |
+|                     |                    | Freight Forwarding Services        |                   |                   | 488510 | 4731 |
+|                     |                    | Moving And Storage Services        |                   |                   | 488510 | 4731 |
+|                     |                    | Postal Services        |                   |                   | 491110 | 4311 |
+|                     | Market Research Services         |                   |                   |                   | 541910 | 8732 |
+|                     | Marketing Services         |                   |                   |                   | 541613 | 8742 |
+|                     |                    | Advertising Services        |                   |                   | 541810 | 7311 |
+|                     |                    | Branding Services        |                   |                   | 541613 | 7311 |
+|                     |                    | Content Marketing Services        |                   |                   | 541613 | 7311 |
+|                     |                    | Content Writing Services        |                   |                   | 541613 | 8742 |
+|                     |                    | Lead Generation Services        |                   |                   | 541810 | 7311 |
+|                     |                    | Public Relations Services        |                   |                   | 541820 | 8743 |
+|                     |                    | Search Engine Marketing Services        |                   |                   | 541613 | 7311 |
+|                     |                    | Social Media Marketing Services        |                   |                   | 541613 | 7311 |
+|                     |                    | Video Production Services        |                   |                   | 512110 | 7812 |
+|                     |                    | Website Design Services        |                   |                   | 541511 | 7371 |
+|                     | Photographic Studios         |                   |                   |                   | 541921 | 7221 |
+|                     | Polling Companies         |                   |                   |                   | 541910 | 8732 |
+|                     | Private Security Companies         |                   |                   |                   | 561612 | 7381 |
+|                     | Recruitment And Staffing Services         |                   |                   |                   | 561311 | 7361 |
+|                     |                    | HR Services Providers        |                   |                   | 541612 | 7361 |
+|                     |                    | PEO Providers        |                   |                   | 561330 | 8742 |
+|                     | Research and Development Organizations         |                   |                   |                   | 541700 | 8731 |
+|                     | Translation Services         |                   |                   |                   | 541930 | 7389 |
+| Public Administration          |                    |                   |                   |                   | 920000 | 9100 |
+|                     | Courts         |                   |                   |                   | 922110 | 9211 |
+|                     | Embassies And Consulates         |                   |                   |                   | 928120 | 9721 |
+|                     | Fire Departments         |                   |                   |                   | 922160 | 9224 |
+|                     | Government Agencies         |                   |                   |                   | 922190 | 9229 |
+|                     |                    | Intelligence Agency        |                   |                   | 928110 | 9711 |
+|                     |                    | Regulatory Agency        |                   |                   | 926150 | 9651 |
+|                     | Government Departments         |                   |                   |                   | 921190 | 9190 |
+|                     | Intergovernmental Organizations         |                   |                   |                   | 928120 | 9721 |
+|                     | International Organizations         |                   |                   |                   | 928120 | 9721 |
+|                     | Local Governments         |                   |                   |                   | 921110 | 9111 |
+|                     | Military Bases         |                   |                   |                   | 928110 | 9711 |
+|                     | Military Related Organizations         |                   |                   |                   | 928110 | 9711 |
+|                     | Ministries         |                   |                   |                   | 921110 | 9111 |
+|                     | Police Departments         |                   |                   |                   | 922120 | 9221 |
+|                     | Political Parties         |                   |                   |                   | 813940 | 8651 |
+| Real Estate Companies          |                    |                   |                   |                   | 531210 | 6531 |
+|                     | Real Estate Investment Management         |                   |                   |                   | 523940 | 6798 |
+|                     | Real Estate Investment Trusts         |                   |                   |                   | 525920 | 6798 |
+| Religious Organizations          |                    |                   |                   |                   | 813110 | 8661 |
+|                     | Places Of Worship         |                   |                   |                   | 813110 | 8661 |
+|                     | Religious Administrative Units         |                   |                   |                   | 813110 | 8661 |
+| Retailers          |                    |                   |                   |                   | 440000 | 5900 |
+|                     | Apparel Retailers         |                   |                   |                   | 458110 | 5651 |
+|                     |                    | Clothing Retailers        |                   |                   | 458000 | 5600 |
+|                     |                    |                   | Children Clothing Retailers        |                   | 458110 | 5640 |
+|                     |                    | Footwear Retailers        |                   |                   | 458210 | 3850 |
+|                     |                    | Lingerie Retailers        |                   |                   | 458110 | 5630 |
+|                     | Auction Houses         |                   |                   |                   | 459999 | 7389 |
+|                     | Automotive Retailers         |                   |                   |                   | 441100 | 5511 |
+|                     |                    | Automotive Part Retailers        |                   |                   | 441330 | 3714 |
+|                     |                    | Vehicle Retailers And Dealership        |                   |                   | 441100 | 5510 |
+|                     | Bookstores         |                   |                   |                   | 459210 | 5942 |
+|                     | Construction Supplies Retailers         |                   |                   |                   | 444100 | 5211 |
+|                     |                    | Floor Covering Retailers        |                   |                   | 449121 | 5713 |
+|                     |                    | Hardware Retailers        |                   |                   | 444140 | 5251 |
+|                     |                    | Plumbing Equipment Retailers        |                   |                   | 444100 | 5211 |
+|                     | Consumer Electronics Retailers         |                   |                   |                   | 449210 | 5940 |
+|                     | Convenience Stores         |                   |                   |                   | 445131 | 5411 |
+|                     | Department Stores         |                   |                   |                   | 455110 | 5311 |
+|                     | Floral Retailers         |                   |                   |                   | 459310 | 5992 |
+|                     | Food Retailers         |                   |                   |                   | 445000 | 5490 |
+|                     |                    | Food Markets        |                   |                   | 445200 | 5490 |
+|                     |                    | Food Trucks        |                   |                   | 722330 | 5963 |
+|                     |                    | Supermarkets        |                   |                   | 445110 | 5411 |
+|                     | Furniture Retailers         |                   |                   |                   | 449110 | 5712 |
+|                     | Gas Station         |                   |                   |                   | 457120 | 5541 |
+|                     | Music Retailers         |                   |                   |                   | 459140 | 5736 |
+|                     | Online Retailers         |                   |                   |                   | 440000 | 5999 |
+|                     | Personal Accessories Retailers         |                   |                   |                   | 458110 | 5900 |
+|                     |                    | Eyewear Retailers        |                   |                   | 456130 | 5995 |
+|                     |                    | Jewelry Retailers        |                   |                   | 458310 | 5944 |
+|                     | Pet Stores         |                   |                   |                   | 459910 | 5999 |
+|                     | Pharmacies         |                   |                   |                   | 456110 | 5910 |
+|                     | Photographic Equipment Stores         |                   |                   |                   | 459410 | 5946 |
+|                     | Sporting Goods Retailers         |                   |                   |                   | 459110 | 5940 |
+|                     | Toy And Video Game Retailers         |                   |                   |                   | 459120 | 5945 |
+|                     | Used Merchandise Retailers         |                   |                   |                   | 459510 | 5932 |
+|                     | Vending Machine Operators         |                   |                   |                   | 445132 | 5962 |
+| Sport Organizations          |                    |                   |                   |                   | 711200 | 7940 |
+|                     | Sports Clubs         |                   |                   |                   | 711211 | 7941 |
+| Technology Companies          |                    |                   |                   |                   |  |  |
+|                     | Autonomous Vehicles         |                   |                   |                   | 336100 | 5012 |
+|                     | Computer Hardware Companies         |                   |                   |                   | 334110 | 5734 |
+|                     |                    | Computer Devices Companies        |                   |                   | 334110 | 3570 |
+|                     |                    | Computer Peripherals Companies        |                   |                   | 334110 | 3577 |
+|                     |                    | Networking Equipment Companies        |                   |                   | 334110 | 3660 |
+|                     |                    | Storage Devices Companies        |                   |                   | 334112 | 3572 |
+|                     | Electronic Products Companies         |                   |                   |                   | 334000 |  |
+|                     |                    | Audio Equipment Manufacturers        |                   |                   | 334310 | 3651 |
+|                     |                    | Cameras Manufacturers        |                   |                   | 334000 | 3861 |
+|                     |                    | Entertainment Systems Companies        |                   |                   | 334310 | 3651 |
+|                     |                    | Mobile Phones Companies        |                   |                   | 334200 | 3660 |
+|                     |                    | Smart Devices Companies        |                   |                   | 334200 | 3660 |
+|                     |                    | Wearable Technology Companies        |                   |                   | 334200 | 3660 |
+|                     | Financial Technology Companies         |                   |                   |                   |  | 6282 |
+|                     |                    | Banking Technology Companies        |                   |                   |  | 6282 |
+|                     |                    | Crowdfunding Technology Companies        |                   |                   |  | 6282 |
+|                     |                    | Cryptocurrency Companies        |                   |                   |  | 6282 |
+|                     | Information Technology Services Companies         |                   |                   |                   | 541500 | 7370 |
+|                     |                    | Development Services Providers        |                   |                   | 541511 | 7371 |
+|                     |                    |                   | Mobile App Development Companies        |                   | 541511 | 7371 |
+|                     |                    |                   | Testing and QA Providers        |                   | 541511 | 7371 |
+|                     |                    |                   | Web Applications Developers        |                   | 541511 | 7371 |
+|                     |                    | Implementation Services Providers        |                   |                   | 541500 | 7370 |
+|                     |                    | Security Services Providers        |                   |                   | 541500 | 7370 |
+|                     | Medical Technology Companies         |                   |                   |                   | 325410 | 5047 |
+|                     | Optics Manufacturing Companies         |                   |                   |                   | 333310 | 3827 |
+|                     | Robotics Companies         |                   |                   |                   | 541511 | 7371 |
+|                     | Semiconductor Companies         |                   |                   |                   | 334410 | 3674 |
+|                     | Software Companies         |                   |                   |                   | 513210 | 7372 |
+|                     |                    | Accounting and Finance Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Accounting Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Accounts Payable Automation Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Billing Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Budgeting and Forecasting Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Expense Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Financial Close Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Financial Wellness Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Invoice Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Order Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Revenue Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Travel Management Software        |                   | 513210 | 7372 |
+|                     |                    | Agriculture Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Apparel Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Artificial Intelligence Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | AI Writing Assistants        |                   | 513210 | 7372 |
+|                     |                    |                   | Computer Vision Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Image Recognition Software        | 513210 | 7372 |
+|                     |                    |                   | Conversational Intelligence Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Chatbots Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Text to Speech Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Voice Recognition Software        | 513210 | 7372 |
+|                     |                    |                   | Data Science and Machine Learning Platforms        |                   | 513210 | 7372 |
+|                     |                    |                   | Natural Language Processing Software        |                   | 513210 | 7372 |
+|                     |                    | Association Management Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Auction Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Automotive Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Aviation Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Blockchain Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Child Care Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Collaboration and Productivity Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Board Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Idea Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Note-Taking Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Objectives and Key Results Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Productivity Bots Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Team Collaboration Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Collaborative Whiteboard Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Employee Intranet Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Meeting Management Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Screen Sharing Software        | 513210 | 7372 |
+|                     |                    |                   | Text Editor Software        |                   | 513210 | 7372 |
+|                     |                    | Commerce Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Communication Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Employee Communications Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Instant Messaging Software        |                   | 513210 | 7372 |
+|                     |                    |                   | VoIP Providers        |                   | 513210 | 7372 |
+|                     |                    |                   | Web Conferencing Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Webinar Platforms        |                   | 513210 | 7372 |
+|                     |                    | Construction Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Content Aggregation Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Bookmarking Tools        |                   | 513210 | 7372 |
+|                     |                    |                   | RSS Feed Readers        |                   | 513210 | 7372 |
+|                     |                    | Content Management Systems        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Cloud Content Collaboration Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Digital Asset Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Digital Experience Platforms        |                   | 513210 | 7372 |
+|                     |                    |                   | Mobile Forms Automation Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Online Form Builder Software        |                   | 513210 | 7372 |
+|                     |                    |                   | User-Generated Content Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Virtual Data Room Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Web Content Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Website Builder Software        |                   | 513210 | 7372 |
+|                     |                    | Creative Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | 3D Design Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | 3D Printing Software        | 513210 | 7372 |
+|                     |                    |                   |                   | CAD Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Virtual Tour Software        | 513210 | 7372 |
+|                     |                    |                   | Audio Editing Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Display Ad Design Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Graphic Design Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Photography Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Software Design Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Stock Media Platforms        |                   | 513210 | 7372 |
+|                     |                    |                   | Video Editing Software        |                   | 513210 | 7372 |
+|                     |                    | Customer Service Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Call &amp; Contact Center Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Conversational Support Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Customer Self-Service Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Customer Success Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Enterprise Feedback Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Experience Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Feedback Analytics Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Field Service Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Help Desk Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Live Chat Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Social Customer Service Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Speech Analytics Software        |                   | 513210 | 7372 |
+|                     |                    | Data Analytics Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Analytics Platforms        |                   | 513210 | 7372 |
+|                     |                    |                   | Business Intelligence Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Data Visualization Tools        |                   | 513210 | 7372 |
+|                     |                    |                   | Enterprise Search Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Predictive Analytics Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Text Analysis Software        |                   | 513210 | 7372 |
+|                     |                    | Data Management Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Data Extraction Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Data Integration Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Data Labeling Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Data Management Tools        |                   | 513210 | 7372 |
+|                     |                    |                   | Data Migration Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Data Quality Tools        |                   | 513210 | 7372 |
+|                     |                    |                   | Data Warehouse Solutions        |                   | 513210 | 7372 |
+|                     |                    |                   | Database Software        |                   | 513210 | 7372 |
+|                     |                    |                   | ETL Tools        |                   | 513210 | 7372 |
+|                     |                    |                   | Knowledge Base Software        |                   | 513210 | 7372 |
+|                     |                    | Data Privacy Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Identity Verification Software        |                   | 513210 | 7372 |
+|                     |                    | Development Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Application Development Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Application Development Platforms        | 513210 | 7372 |
+|                     |                    |                   |                   | Cloud Platform as a Service Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Integrated Development Environments        | 513210 | 7372 |
+|                     |                    |                   |                   | Low-Code Development Platforms        | 513210 | 7372 |
+|                     |                    |                   |                   | Mobile Development Software        | 513210 | 7372 |
+|                     |                    |                   |                   | No-Code Development Platforms        | 513210 | 7372 |
+|                     |                    |                   |                   | Web Frameworks        | 513210 | 7372 |
+|                     |                    |                   | DevOps Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | AIOps Tools        | 513210 | 7372 |
+|                     |                    |                   |                   | Automation Testing        | 513210 | 7372 |
+|                     |                    |                   |                   | Bug Tracking Software        | 513210 | 7372 |
+|                     |                    |                   |                   | CI&#x2F;CD Tools        | 513210 | 7372 |
+|                     |                    |                   |                   | Containerization Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Load Testing Tools        | 513210 | 7372 |
+|                     |                    |                   |                   | Version Control Software        | 513210 | 7372 |
+|                     |                    |                   | Software Testing Tools        |                   | 513210 | 7372 |
+|                     |                    | Digital Advertising Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Cross-Channel Advertising Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Data Management Platforms        |                   | 513210 | 7372 |
+|                     |                    |                   | Demand Side Platform        |                   | 513210 | 7372 |
+|                     |                    |                   | Display Advertising Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Mobile Advertising Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Publisher Ad Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Search Advertising Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Social Media Advertising Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Video Advertising Software        |                   | 513210 | 7372 |
+|                     |                    | E-Commerce Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Catalog Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Drop Shipping Software        |                   | 513210 | 7372 |
+|                     |                    |                   | E-Commerce Analytics Software        |                   | 513210 | 7372 |
+|                     |                    |                   | E-Commerce Personalization Software        |                   | 513210 | 7372 |
+|                     |                    |                   | E-Commerce Platforms        |                   | 513210 | 7372 |
+|                     |                    |                   | E-Commerce Search Software        |                   | 513210 | 7372 |
+|                     |                    |                   | E-Commerce Tools        |                   | 513210 | 7372 |
+|                     |                    |                   | E-commerce Fraud Protection Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Marketplace Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Mobile E-Commerce Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Multichannel Retail Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Online Marketplace Optimization Tools        |                   | 513210 | 7372 |
+|                     |                    |                   | Product Information Management Systems        |                   | 513210 | 7372 |
+|                     |                    |                   | Review Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Subscription Management Software        |                   | 513210 | 7372 |
+|                     |                    | Education Management Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Learning Management Systems        |                   | 513210 | 7372 |
+|                     |                    |                   | Library Management Systems        |                   | 513210 | 7372 |
+|                     |                    |                   | Mentoring Software        |                   | 513210 | 7372 |
+|                     |                    |                   | School Management Software        |                   | 513210 | 7372 |
+|                     |                    | Education Platforms        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Code Development Education Platforms        |                   | 513210 | 7372 |
+|                     |                    |                   | Language Education Platforms        |                   | 513210 | 7372 |
+|                     |                    |                   | Training eLearning Software        |                   | 513210 | 7372 |
+|                     |                    | Energy Management Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Equipment Rental Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Event Management Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Financial Services Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Financial Analytics Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Insurance Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Investment Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Loan Software        |                   | 513210 | 7372 |
+|                     |                    | Fitness Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Food Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Fundraising Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Grant Management Software        |                   |                   | 513210 | 7372 |
+|                     |                    | HR Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Benefits Administration Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Compensation Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Corporate Performance Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Employee Engagement Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Employee Monitoring Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Employee Recognition Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Employee Scheduling Software        |                   | 513210 | 7372 |
+|                     |                    |                   | HR Analytics Software        |                   | 513210 | 7372 |
+|                     |                    |                   | HR Case Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Job Board Platforms        |                   | 513210 | 7372 |
+|                     |                    |                   | Payroll Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Performance Management Systems        |                   | 513210 | 7372 |
+|                     |                    |                   | Portfolio Board Platforms        |                   | 513210 | 7372 |
+|                     |                    |                   | Recruiting Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Applicant Tracking Systems        | 513210 | 7372 |
+|                     |                    |                   |                   | Employee Referral Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Onboarding Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Pre-Employment Screening Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Recruiting Automation Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Talent Acquisition Suites Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Technical Skills Screening Software        | 513210 | 7372 |
+|                     |                    |                   | Talent Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Time Tracking Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Workforce Management Software        |                   | 513210 | 7372 |
+|                     |                    | Health Care Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Clinical Communication and Collaboration Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Clinical Documentation Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Disease Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | EHR Software        |                   | 513210 | 7372 |
+|                     |                    |                   | HIPAA Compliant Messaging Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Healthcare Analytics Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Healthcare Claims Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Healthcare HR Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Home Health Care Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Medical 3D Visualization Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Medical Billing Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Medical Practice Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Medical Transcription Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Mental Health Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Patient Experience Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Pharmacy Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Population Health Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Provider Data Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Radiology Information Systems        |                   | 513210 | 7372 |
+|                     |                    |                   | Revenue Cycle Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Telemedicine Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Wellness Software        |                   | 513210 | 7372 |
+|                     |                    | Hospitality Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Hotel Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Reservation Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Restaurant Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Spa and Salon Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Vacation Rental Platforms        |                   | 513210 | 7372 |
+|                     |                    | Hosting Providers        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Content Delivery Network Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Domain Registration Providers        |                   | 513210 | 7372 |
+|                     |                    |                   | Managed DNS Providers Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Web Hosting Providers        |                   | 513210 | 7372 |
+|                     |                    | IT Infrastructure Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Cloud File Storage Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Data Center Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Data Recovery Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Backup Software        | 513210 | 7372 |
+|                     |                    |                   | Data Transfer Tools        |                   | 513210 | 7372 |
+|                     |                    |                   | Load Balancing Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Monitoring Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Application Performance Monitoring Tools        | 513210 | 7372 |
+|                     |                    |                   |                   | Cloud Infrastructure Monitoring Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Database Monitoring Tools        | 513210 | 7372 |
+|                     |                    |                   |                   | Enterprise Monitoring Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Log Monitoring Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Network Monitoring Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Server Monitoring Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Website Monitoring Software        | 513210 | 7372 |
+|                     |                    |                   | Network Management Tools        |                   | 513210 | 7372 |
+|                     |                    |                   | Operating Systems        |                   | 513210 | 7372 |
+|                     |                    |                   | Remote Desktop Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Remote Support Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Server Virtualization Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Storage Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Virtual Desktop Infrastructure Software        |                   | 513210 | 7372 |
+|                     |                    | IT Management Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Application Portfolio Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Cloud Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Data Governance Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Enterprise Mobility Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | IT Asset Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | IT Service Management Tools        |                   | 513210 | 7372 |
+|                     |                    |                   | Incident Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Mobile Device Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | OCR Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Process Automation Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Business Process Management Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Digital Process Automation Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Robotic Process Automation Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Workflow Management Software        | 513210 | 7372 |
+|                     |                    | IoT Management Platforms        |                   |                   | 513210 | 7372 |
+|                     |                    | Laboratory Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Legal Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Life Sciences Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Logistics Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Distribution Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Inventory Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Shipping Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Supply Chain Management Software        |                   | 513210 | 7372 |
+|                     |                    | Marine Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Marketing Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Account-Based Marketing Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Account-Based Data Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Account-Based Execution Software        | 513210 | 7372 |
+|                     |                    |                   | Affiliate Marketing Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Audience Response Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Content Marketing Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Content Analytics Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Content Creation Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Content Curation Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Content Distribution Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Content Experience Platforms        | 513210 | 7372 |
+|                     |                    |                   | Conversational Marketing Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Conversion Rate Optimization Tools        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Landing Page Builders        | 513210 | 7372 |
+|                     |                    |                   |                   | Product Analytics Software        | 513210 | 7372 |
+|                     |                    |                   | Customer Data Platforms        |                   | 513210 | 7372 |
+|                     |                    |                   | Customer Journey Analytics Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Demand Generation Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Brand Advocacy Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Lead Generation Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Loyalty Management Software        | 513210 | 7372 |
+|                     |                    |                   | Digital Analytics Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Digital Signage Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Email Deliverability Tools        |                   | 513210 | 7372 |
+|                     |                    |                   | Email Marketing Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Email Template Builder Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Inbound Call Tracking Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Local Marketing Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Market Intelligence Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Marketing Analytics Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Marketing Automation Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Marketing Resource Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Mobile Marketing Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Online Community Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Online Reputation Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Personalization Engines        |                   | 513210 | 7372 |
+|                     |                    |                   | Personalization Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Print Fulfillment Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Public Relations Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Media Monitoring Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Media and Influencer Targeting Software        | 513210 | 7372 |
+|                     |                    |                   | Push Notification Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Rewards and Incentives Software        |                   | 513210 | 7372 |
+|                     |                    |                   | SEO Tools        |                   | 513210 | 7372 |
+|                     |                    |                   | SMS Marketing Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Social Media Marketing Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Influencer Marketing Platforms        | 513210 | 7372 |
+|                     |                    |                   |                   | Social Media Analytics Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Social Media Management Tools        | 513210 | 7372 |
+|                     |                    |                   |                   | Social Media Monitoring Tools        | 513210 | 7372 |
+|                     |                    |                   | Transactional Email Software        |                   | 513210 | 7372 |
+|                     |                    |                   | User Research Software        |                   | 513210 | 7372 |
+|                     |                    | Nonprofit Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Office Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Calendar Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Document Creation Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Document Generation Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Email Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Emergency Notification Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Meeting Room Booking Systems        |                   | 513210 | 7372 |
+|                     |                    |                   | Online Appointment Scheduling Software        |                   | 513210 | 7372 |
+|                     |                    |                   | PDF Editor Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Presentation Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Survey Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Visitor Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Writing Assistants Software        |                   | 513210 | 7372 |
+|                     |                    | Oil and Gas Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Open Source Software Companies        |                   |                   | 513210 | 7372 |
+|                     |                    | Parking Management Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Parks and Recreation Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Physical Security Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Political Campaign Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Property Management Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Public Safety Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Real Estate Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Retail Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Sales Tools        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | AI Sales Assistant Software        |                   | 513210 | 7372 |
+|                     |                    |                   | CRM Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Contract Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | E-Signature Software        |                   | 513210 | 7372 |
+|                     |                    |                   | ERP Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Asset Management Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Environmental Health and Safety Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Manufacturing Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Procurement Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Product Management Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Professional Services Automation Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Project Management Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Quality Management Systems        | 513210 | 7372 |
+|                     |                    |                   |                   | Strategy And Innovation Roadmapping Tools        | 513210 | 7372 |
+|                     |                    |                   | Field Sales Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Partner Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Quote Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Sales Acceleration Software        |                   | 513210 | 7372 |
+|                     |                    |                   |                   | Email Tracking Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Outbound Call Tracking Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Sales Coaching Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Sales Conversation Intelligence Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Sales Enablement Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Sales Engagement Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Sales Performance Management Software        | 513210 | 7372 |
+|                     |                    |                   |                   | Sales Training and Onboarding Software        | 513210 | 7372 |
+|                     |                    |                   | Sales Analytics Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Sales Gamification Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Sales Intelligence Software        |                   | 513210 | 7372 |
+|                     |                    | Security Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Antivirus Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Cloud Security Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Data Security Software        |                   | 513210 | 7372 |
+|                     |                    |                   | DevSecOps Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Email Security Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Encryption Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Endpoint Protection Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Identity Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Network Security Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Risk Assessment Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Security Awareness Training Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Vulnerability Management Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Web Security Software        |                   | 513210 | 7372 |
+|                     |                    | Social Network Platforms        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Dating Platforms        |                   | 513210 | 7372 |
+|                     |                    | Software As A Service Companies        |                   |                   | 513210 | 7372 |
+|                     |                    | Sports Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Sustainability Management Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Tickets Registration Platforms        |                   |                   | 513210 | 7372 |
+|                     |                    | Translation Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Travel Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Veterinary Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Video Software        |                   |                   | 513210 | 7372 |
+|                     |                    |                   | Live Stream Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Video CMS Software        |                   | 513210 | 7372 |
+|                     |                    |                   | Video Hosting Platforms        |                   | 513210 | 7372 |
+|                     |                    | Virtual and Augmented Reality Software        |                   |                   | 513210 | 7372 |
+|                     |                    | Waste Management Software        |                   |                   | 513210 | 7372 |
+|                     | Telecommunications Companies         |                   |                   |                   | 517110 | 4800 |
+|                     |                    | Internet Service Providers        |                   |                   | 517110 | 7375 |
+|                     |                    | Telco Infrastructure Equipment Companies        |                   |                   | 517110 | 4800 |
+|                     | Video Game Companies         |                   |                   |                   | 513210 | 7372 |
+| Transport Companies          |                    |                   |                   |                   | 480000 | 4729 |
+|                     | Airlines         |                   |                   |                   | 481111 | 4512 |
+|                     | Ferry Companies         |                   |                   |                   | 483212 | 4489 |
+|                     | Public Transport Operators         |                   |                   |                   | 485110 | 4729 |
+|                     | Railway Companies         |                   |                   |                   | 482110 | 4000 |
+|                     | Ridesharing And Taxi Companies         |                   |                   |                   | 485310 | 4121 |
+|                     | Vehicle Rental Companies         |                   |                   |                   | 532111 | 7514 |
+| Utility Companies          |                    |                   |                   |                   | 221000 | 4900 |
+|                     | Electricity Distribution Companies         |                   |                   |                   | 221122 | 4911 |
+|                     | Gas Distribution Companies         |                   |                   |                   | 221210 | 4924 |
+|                     | Heat Distribution Companies         |                   |                   |                   | 221330 | 4961 |
+|                     | Waste And Recycling Companies         |                   |                   |                   | 562000 | 4953 |
+|                     |                    | Recycling Companies        |                   |                   | 562920 | 4953 |
+|                     | Water Distribution Companies         |                   |                   |                   | 221310 | 4941 |
diff --git a/docs/kg-ont-JobPost.md b/docs/kg-ont-JobPost.md
new file mode 100644
index 00000000..fd645e86
--- /dev/null
+++ b/docs/kg-ont-JobPost.md
@@ -0,0 +1,559 @@
+---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
+id: kg-ont-JobPost
+title: JobPost
+generatedBy: generateOntology.js
+---
+
+The Job Post entity type encompasses all job postings found throughout the web and known to the Knowledge Graph. 
+
+Note that fields are not guaranteed to exist in every entity record.
+
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
+
+## JobPost Fields
+* [allDescriptions](#alldescriptions) 
+* [allNames](#allnames) 
+* [allOriginHashes](#alloriginhashes) 
+* [allUriDetails](#alluridetails) 
+* [allUris](#alluris) 
+* [crawlTimestamp](#crawltimestamp) 
+* [date](#date) 
+* [description](#description) 
+* [descriptors](#descriptors) 
+* [diffbotUri](#diffboturi) 
+* [employer](#employer) 
+* [id](#id) 
+* [image](#image) 
+* [images](#images) 
+* [importance](#importance) 
+* [jobCategories](#jobcategories) 
+* [language](#language) 
+* [locations](#locations) 
+* [name](#name) 
+* [nbIncomingEdges](#nbincomingedges) 
+* [nbOrigins](#nborigins) 
+* [nonCanonicalFacts](#noncanonicalfacts) 
+* [originDetails](#origindetails) 
+* [origins](#origins) 
+* [remote](#remote) 
+* [requirements](#requirements) 
+* [skills](#skills) 
+* [summary](#summary) 
+* [tasks](#tasks) 
+* [type](#type) 
+* [types](#types) 
+* [wikipediaPageviews](#wikipediapageviews) 
+* [wikipediaPageviewsGrowth](#wikipediapageviewsgrowth) 
+* [wikipediaPageviewsLastQuarter](#wikipediapageviewslastquarter) 
+* [wikipediaPageviewsLastQuarterGrowth](#wikipediapageviewslastquartergrowth) 
+* [wikipediaPageviewsLastYear](#wikipediapageviewslastyear) 
+* [wikipediaPageviewsLastYearGrowth](#wikipediapageviewslastyeargrowth) 
+
+## JobPost Field Details
+Note that certain longer field examples may be truncated for readability.
+
+### allDescriptions
+  All descriptions found for this entity. For the best description, refer to the field &#39;description&#39;.
+* **Type:** String
+* **Example:**
+```
+{
+	"allDescriptions": [
+		"Machine Learning Engineer (Applied)\nMachine Learning Engineers in our applied division design and build massively scaled systems that power the core of Diffbot’s autonomous knowledge extraction system. You’ll work with some of the world’s most premier researchers in their field, both at Diffbot and in academic AI labs, to implement state-of-the-art models in our production datacenter.\nResponsibilities\nImprove accuracy of our production machine learning systems by applying the latest published research, feature engineering, and tuning of model hyperparameters\nOwn end-to-end accuracy and performance for our 60+ machine learning problems\nBe up to date on the latest research publications, and rapidly assess the latest results for production and scalability potential\nWork closely with product leadership and customers on training datasets and error analysis\nRequirements\nMasters in Computer Science or equivalent work experience\n5+ years of industry experience designing and developing software\nExperience implementing the latest machine learning algorithms from papers\nExperience in designing performant production systems\nProduction/deployment engineering in java\nPreferred Skills\n2+ years Java, C++, C#\nPublished research in CV/NLP topics\nPhD in Computer Science\nDiffbot is a group of ML researchers and engineers based in Menlo Park, California and we've developed an autonomous knowledge extraction system that is performing at better-than-human levels of...\nApply Now"
+	]
+}
+```
+### allNames
+  All names used, including nicknames, full names and transliterations to other languages.
+* **Type:** String
+* **Example:**
+```
+{
+	"allNames": [
+		"Machine Learning Engineer, Applied"
+	]
+}
+```
+### allOriginHashes
+  For Diffbot&#39;s internal use only.
+* **Type:** String
+* **Example:**
+```
+{
+	"allOriginHashes": [
+		"NKjRXSj2PPCadIWMDwNLDQ"
+	]
+}
+```
+### allUriDetails
+  Additional information about each URI in &#39;allUris&#39;, which lists the URIs associated with this entity.
+* **Type:** UriDetails
+* **Example:**
+```
+{
+	"allUriDetails": [
+		{
+			"domainMonthlyTrafficGrowth": "",
+			"domainMonthlyTraffic": 0,
+			"redirectsTo": "",
+			"nbFollowing": 0,
+			"uriType": "",
+			"verified": false,
+			"nbLinkedAccounts": 0,
+			"nbFollowers": 0,
+			"httpCodeTimestamp": 0,
+			"httpCode": "",
+			"uri": ""
+		}
+	]
+}
+```
+### allUris
+  All URIs associated with an entity. A URI (uniform resource identifier) is a page on the web that describes an entity (e.g., an company&#39;s homepage or a person&#39;s social network profile).
+* **Type:** URL
+* **Example:**
+```
+{
+	"allUris": [
+		"womentech.net/job/diffbot/menlo-park/machine-learning-engineer-applied"
+	]
+}
+```
+### crawlTimestamp
+  The default crawlTimestamp is the most recent date of all of the crawlTimestamps of the origins used to compute the Entity, returned as a UNIX time.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"crawlTimestamp": 1727999253
+}
+```
+### date
+  The date when this job is posted online
+* **Type:** DDate
+* **Example:**
+```
+{
+	"date": {
+		"str": "d2024-10-03",
+		"precision": 3,
+		"timestamp": 1727913600000
+	}
+}
+```
+### description
+  A few sentences describing an entity
+* **Type:** String
+* **Example:**
+```
+{
+	"description": "Machine Learning Engineer (Applied)\nMachine Learning Engineers in our applied division design and build massively scaled systems that power the core of Diffbot’s autonomous knowledge extraction system. You’ll work with some of the world’s most premier researchers in their field, both at Diffbot and in academic AI labs, to implement state-of-the-art models in our production datacenter.\nResponsibilities\nImprove accuracy of our production machine learning systems by applying the latest published research, feature engineering, and tuning of model hyperparameters\nOwn end-to-end accuracy and performance for our 60+ machine learning problems\nBe up to date on the latest research publications, and rapidly assess the latest results for production and scalability potential\nWork closely with product leadership and customers on training datasets and error analysis\nRequirements\nMasters in Computer Science or equivalent work experience\n5+ years of industry experience designing and developing software\nExperience implementing the latest machine learning algorithms from papers\nExperience in designing performant production systems\nProduction/deployment engineering in java\nPreferred Skills\n2+ years Java, C++, C#\nPublished research in CV/NLP topics\nPhD in Computer Science\nDiffbot is a group of ML researchers and engineers based in Menlo Park, California and we've developed an autonomous knowledge extraction system that is performing at better-than-human levels of...\nApply Now"
+}
+```
+### descriptors
+  A list of free-form keywords describing this entity
+* **Type:** String
+* **Example:**
+```
+{
+	"descriptors": ""
+}
+```
+### diffbotUri
+  diffbotUri is the URI an entity&#39;s  (URI), which is defined by appending the Diffbot ID to the URL https:&#x2F;&#x2F;diffbot.com&#x2F;entity&#x2F;. For example, Diffbot&#39;s entityID is CWSwJ_SWQPfqO3HQsxY4lGg and its DiffbotUri is https:&#x2F;&#x2F;diffbot.com&#x2F;entity&#x2F;CWSwJ_SWQPfqO3HQsxY4lGg
+* **Type:** URL
+* **Example:**
+```
+{
+	"diffbotUri": "http://diffbot.com/entity/ENKjRXSj2PPCadIWMDwNLDQ"
+}
+```
+### employer
+  The employer of this job
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"employer": {
+		"summary": "American machine learning and knowledge management company",
+		"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0Stn8p.%5DjEp9G.Bd%7Bk%3EXMJM5%7E%7B-E%2FXy-Z7%5Dq-CdLD-axttB6p%2FR620zN_%3Cb4E.A%5Dm",
+		"types": [
+			"Organization",
+			"Corporation",
+			"Company"
+		],
+		"name": "Diffbot",
+		"diffbotUri": "http://diffbot.com/entity/EYX1i02YVPsuT7fPLUYgRhQ",
+		"targetDiffbotId": "EYX1i02YVPsuT7fPLUYgRhQ",
+		"type": "Organization"
+	}
+}
+```
+### id
+  An alphanumeric string like CWSwJ_SWQPfqO3HQsxY4lGg that uniquely identifies an entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"id": "ENKjRXSj2PPCadIWMDwNLDQ"
+}
+```
+### image
+  The main image used to represent the entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"image": ""
+}
+```
+### images
+  The visual representation of an entity usually in the form of a png, jpeg, gif, or svg file.
+* **Type:** ImageField
+* **Example:**
+```
+{
+	"images": [
+		{
+			"classifications": "",
+			"fingerprint": "",
+			"title": "",
+			"isCached": false,
+			"url": ""
+		}
+	]
+}
+```
+### importance
+  A number between 0 and 100 indicating how important or popular an entity is.
+* **Type:** Float
+* **Example:**
+```
+{
+	"importance": 4.84171199798584
+}
+```
+### jobCategories
+  Employment categories for this job post. See the taxonomy &#x60;Employment Categories&#x60; for possible values.
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"jobCategories": [
+		{
+			"name": "Artificial Intelligence",
+			"diffbotUri": "http://diffbot.com/entity/ESsRhWRXQP4y38EZrrH8I6A",
+			"targetDiffbotId": "ESsRhWRXQP4y38EZrrH8I6A",
+			"type": "EmploymentCategory"
+		},
+		{
+			"name": "Engineering, IT and Software Development",
+			"diffbotUri": "http://diffbot.com/entity/EphfPPRLfN4yo0a952UCnDA",
+			"targetDiffbotId": "EphfPPRLfN4yo0a952UCnDA",
+			"type": "EmploymentCategory"
+		}
+	]
+}
+```
+### language
+  Refers to the humanLanguage in which a Job is written
+* **Type:** Language
+* **Example:**
+```
+{
+	"language": {}
+}
+```
+### locations
+  Locations of the jobs
+* **Type:** Location
+* **Example:**
+```
+{
+	"locations": [
+		{
+			"country": {
+				"summary": "Country located primarily in North America",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ",
+				"types": [
+					"Place",
+					"AdministrativeArea",
+					"Country"
+				],
+				"name": "United States",
+				"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
+				"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
+				"type": "Place"
+			},
+			"address": "Menlo Park, California",
+			"city": {
+				"summary": "City in San Mateo County, California, United States",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FjvIT%3Ei%5DC%5Bw%3Bq9%40G%3Dg%7BGewNxOd%5EE%7EL_1b%2F%40Q.Yu5",
+				"types": [
+					"Place",
+					"AdministrativeArea",
+					"City"
+				],
+				"name": "Menlo Park",
+				"diffbotUri": "http://diffbot.com/entity/EQiAUr370NpW1gvx-V4fTrQ",
+				"targetDiffbotId": "EQiAUr370NpW1gvx-V4fTrQ",
+				"type": "Place"
+			},
+			"metroArea": {
+				"summary": "Metropolitan area in California, United States",
+				"types": [
+					"Place",
+					"AdministrativeArea"
+				],
+				"name": "San Francisco Bay Area",
+				"diffbotUri": "http://diffbot.com/entity/E9vk_v1rKPgitvjkH--IN8w",
+				"targetDiffbotId": "E9vk_v1rKPgitvjkH--IN8w",
+				"type": "Place"
+			},
+			"subregion": {
+				"summary": "County in California, United States",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FEvtr%3ErO%3CLr2Y%5EBfA_%7EJt%40NeLn2L%7EL%60zdzEW%7DBf%3C%5BjDp%3FjpmwN%5D%7C_.%40%5C%7B",
+				"types": [
+					"Place",
+					"AdministrativeArea",
+					"Subregion"
+				],
+				"name": "San Mateo County",
+				"diffbotUri": "http://diffbot.com/entity/E3vHP---hM4eCDOBsK0fhKA",
+				"targetDiffbotId": "E3vHP---hM4eCDOBsK0fhKA",
+				"type": "Place"
+			},
+			"latitude": 37.49946975708008,
+			"precision": 6.71204948425293,
+			"region": {
+				"summary": "State of the United States of America",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FEvtr%3EnAo-8UY%5EBfA_%7EJt%40N%2CCS0ZsGZqQ%2F%3BO%3C%5EwBd2Uj9HvRq%3C%5E.Pw4",
+				"types": [
+					"Place",
+					"AdministrativeArea",
+					"Region"
+				],
+				"name": "California",
+				"diffbotUri": "http://diffbot.com/entity/El0_8ehooNxOPT36Y4RdV9w",
+				"targetDiffbotId": "El0_8ehooNxOPT36Y4RdV9w",
+				"type": "Place"
+			},
+			"longitude": -122.14386749267578
+		}
+	]
+}
+```
+### name
+  Primary text label for this entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"name": "Machine Learning Engineer, Applied"
+}
+```
+### nbIncomingEdges
+  This is the number of edges in the Knowledge Graph that point to this entity. For example, the nbIncomingEdges field for Google is over 100,000. This number includes the number of people that work at google, the number of investors who invested in google, etc.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"nbIncomingEdges": 0
+}
+```
+### nbOrigins
+  Total number of origins in the field &#39;origins&#39;. This field is only available in extended JSON mode.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"nbOrigins": 1
+}
+```
+### nonCanonicalFacts
+  Enumerates all the non-canonical fields (i.e., those not defined in the ontology) that have a value for this entity. For instance, if &#39;numberOfChildren&#39; is listed in &#39;nonCanonicalFacts&#39; then the entity JSON will have the key &#39;numberOfChildren&#39; with an associated value. This field is only provided when the parameter nonCanonicalFacts&#x3D;1 is set. See: https:&#x2F;&#x2F;docs.diffbot.com&#x2F;kgapi
+* **Type:** String
+* **Example:**
+```
+{
+	"nonCanonicalFacts": ""
+}
+```
+### originDetails
+  Additional information about origins listed in &#39;origins&#39;, including the latest time it was crawled. This field is only available in extended JSON mode.
+* **Type:** OriginDetail
+* **Example:**
+```
+{
+	"originDetails": [
+		{
+			"crawledAt": {
+				"str": "",
+				"precision": 0,
+				"timestamp": 0
+			},
+			"origin": ""
+		}
+	]
+}
+```
+### origins
+  An origin is a web address where Diffbot found one or more facts about an entity. This field is only available in extended JSON mode.
+* **Type:** String
+* **Example:**
+```
+{
+	"origins": [
+		"womentech.net/job/diffbot/menlo-park/machine-learning-engineer-applied"
+	]
+}
+```
+### remote
+  whether this job is remote, possible values: {REMOTE, NOT_REMOTE, HYBRID, UNDEFINED}
+* **Type:** Remote
+* **Example:**
+```
+{
+	"remote": {}
+}
+```
+### requirements
+  Description of the job
+* **Type:** String
+* **Example:**
+```
+{
+	"requirements": [
+		"Masters in Computer Science or equivalent work experience",
+		"5+ years of industry experience designing and developing software",
+		"Experience implementing the latest machine learning algorithms from papers"
+	]
+}
+```
+### skills
+  The list of required skills for this job post
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"skills": [
+		{
+			"name": "computer science",
+			"diffbotUri": "http://diffbot.com/entity/EH62PPoEHNzGEtJysOxqiiA",
+			"targetDiffbotId": "EH62PPoEHNzGEtJysOxqiiA"
+		},
+		{
+			"name": "knowledge discovery",
+			"diffbotUri": "http://diffbot.com/entity/ET8Z4SIHrNgercKJwF2qkmQ",
+			"targetDiffbotId": "ET8Z4SIHrNgercKJwF2qkmQ"
+		},
+		{
+			"name": "machine learning",
+			"diffbotUri": "http://diffbot.com/entity/ECPZuuTwvMXGfGmvJ33T2IQ",
+			"targetDiffbotId": "ECPZuuTwvMXGfGmvJ33T2IQ"
+		}
+	]
+}
+```
+### summary
+  A short phrase designed to disambiguate entities with the same or similar name
+* **Type:** String
+* **Example:**
+```
+{
+	"summary": ""
+}
+```
+### tasks
+  Description of the job
+* **Type:** String
+* **Example:**
+```
+{
+	"tasks": [
+		"Improve accuracy of our production machine learning systems by applying the latest published research, feature engineering, and tuning of model hyperparameters",
+		"Own end-to-end accuracy and performance for our 60+ machine learning problems",
+		"Be up to date on the latest research publications, and rapidly assess the latest results for production and scalability potential"
+	]
+}
+```
+### type
+  The top-level type of a Diffbot entity. Examples of type include Person, Organization, Article, Product.
+* **Type:** Type
+* **Example:**
+```
+{
+	"type": "JobPost"
+}
+```
+### types
+  All types of a Diffbot entity, including the value of the field &#39;type&#39;.
+* **Type:** String
+* **Example:**
+```
+{
+	"types": [
+		"JobPost"
+	]
+}
+```
+### wikipediaPageviews
+  The number of views of its Wikipedia page of the last month if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviews": 0
+}
+```
+### wikipediaPageviewsGrowth
+  The month over month growth of wikipediaPageviews, where we count the increment of the number of page views of the second to last (full) month, compared with that of the last (full) month. if today was Aug 16th, 2022, the last complete month is July. So it refers to the increment from June to July, i.e., ( f(July) - f(June) ) ÷ f(June) x 100%. The f(.) only counts the first 28 days of a month, to avoid fluctuations between 31-days months like Jan and 28(29)-days months like Feb.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsGrowth": ""
+}
+```
+### wikipediaPageviewsLastQuarter
+  The number of views of its Wikipedia page of the last quarter if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastQuarter": 0
+}
+```
+### wikipediaPageviewsLastQuarterGrowth
+  The quarter over quarter growth of wikipediaPageviews, where we count the increment of the number of page views of the second to last (full) quarter, compared with that of the last (full) quarter. If today was Aug 16th, 2022, the last complete quarter is Q2 (April, May, June). So it refers to the increment from Q1 to Q2, i.e., ( f(Q2) - f(Q1) ) ÷ f(Q1) x 100%.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastQuarterGrowth": ""
+}
+```
+### wikipediaPageviewsLastYear
+  The number of views of its Wikipedia page of the last year if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastYear": 0
+}
+```
+### wikipediaPageviewsLastYearGrowth
+  The year over year growth of wikipediaPageviews, where we count the monthly-rolling increment of the year before last than the last year. It today was Aug 16th, 2022, it is computed by comparing the numbers from Aug 2021 to July 2022 and from Aug 2020 to July 2021, i.e., ( f(Aug 2021 to July 2022) - f(Aug 2020 to July 2021) ) ÷ f(Aug 2020 to July 2021) x 100%.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastYearGrowth": ""
+}
+```
diff --git a/docs/kg-ont-LegalEntity.md b/docs/kg-ont-LegalEntity.md
new file mode 100644
index 00000000..f81a90b2
--- /dev/null
+++ b/docs/kg-ont-LegalEntity.md
@@ -0,0 +1,813 @@
+---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
+id: kg-ont-legalentity
+title: LegalEntity
+generatedBy: generateOntology.js
+---
+
+The LegalEntity entity type includes companies and organizations with legal status and identifiers.
+
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
+
+## LegalEntity Fields
+* [allDescriptions](#alldescriptions) 
+* [allNames](#allnames) 
+* [allOriginHashes](#alloriginhashes) 
+* [allUriDetails](#alluridetails) 
+* [allUris](#alluris) 
+* [bicCodes](#biccodes) 
+* [category](#category) 
+* [crawlTimestamp](#crawltimestamp) 
+* [description](#description) 
+* [descriptors](#descriptors) 
+* [diffbotUri](#diffboturi) 
+* [expirationReason](#expirationreason) 
+* [from](#from) 
+* [gleifId](#gleifid) 
+* [id](#id) 
+* [image](#image) 
+* [images](#images) 
+* [importance](#importance) 
+* [isCurrent](#iscurrent) 
+* [isinCodes](#isincodes) 
+* [legalFormCode](#legalformcode) 
+* [legalFormName](#legalformname) 
+* [legalJurisdiction](#legaljurisdiction) 
+* [location](#location) 
+* [locations](#locations) 
+* [micCodes](#miccodes) 
+* [name](#name) 
+* [nbIncomingEdges](#nbincomingedges) 
+* [nbOrigins](#nborigins) 
+* [nonCanonicalFacts](#noncanonicalfacts) 
+* [originDetails](#origindetails) 
+* [origins](#origins) 
+* [parent](#parent) 
+* [registerName](#registername) 
+* [registrationAuthority](#registrationauthority) 
+* [relationships](#relationships) 
+* [subCategory](#subcategory) 
+* [subsidiaries](#subsidiaries) 
+* [successorEntity](#successorentity) 
+* [summary](#summary) 
+* [to](#to) 
+* [type](#type) 
+* [types](#types) 
+* [ultimateParent](#ultimateparent) 
+* [wikipediaPageviews](#wikipediapageviews) 
+* [wikipediaPageviewsGrowth](#wikipediapageviewsgrowth) 
+* [wikipediaPageviewsLastQuarter](#wikipediapageviewslastquarter) 
+* [wikipediaPageviewsLastQuarterGrowth](#wikipediapageviewslastquartergrowth) 
+* [wikipediaPageviewsLastYear](#wikipediapageviewslastyear) 
+* [wikipediaPageviewsLastYearGrowth](#wikipediapageviewslastyeargrowth) 
+
+## LegalEntity Field Details
+Note that certain longer field examples may be truncated for readability.
+
+### allDescriptions
+  All descriptions found for this entity. For the best description, refer to the field &#39;description&#39;.
+* **Type:** String
+* **Example:**
+```
+{
+	"allDescriptions": ""
+}
+```
+### allNames
+  All names used, including nicknames, full names and transliterations to other languages.
+* **Type:** String
+* **Example:**
+```
+{
+	"allNames": [
+		"GENERAL MOTORS COMPANY"
+	]
+}
+```
+### allOriginHashes
+  For Diffbot&#39;s internal use only.
+* **Type:** String
+* **Example:**
+```
+{
+	"allOriginHashes": [
+		"d-KtAaRBO8G1urmPKsSE6g"
+	]
+}
+```
+### allUriDetails
+  Additional information about each URI in &#39;allUris&#39;, which lists the URIs associated with this entity.
+* **Type:** UriDetails
+* **Example:**
+```
+{
+	"allUriDetails": [
+		{
+			"domainMonthlyTrafficGrowth": "",
+			"domainMonthlyTraffic": 0,
+			"redirectsTo": "",
+			"nbFollowing": 0,
+			"uriType": "",
+			"verified": false,
+			"nbLinkedAccounts": 0,
+			"nbFollowers": 0,
+			"httpCodeTimestamp": 0,
+			"httpCode": "",
+			"uri": ""
+		}
+	]
+}
+```
+### allUris
+  All URIs associated with an entity. A URI (uniform resource identifier) is a page on the web that describes an entity (e.g., an company&#39;s homepage or a person&#39;s social network profile).
+* **Type:** URL
+* **Example:**
+```
+{
+	"allUris": [
+		"gleif.org/54930070NSV60J38I987"
+	]
+}
+```
+### bicCodes
+  BIC number or SWIFT code — is a standard format for Business Identifier Codes (BIC). It&#39;s used to identify banks and financial institutions.
+* **Type:** String
+* **Example:**
+```
+{
+	"bicCodes": ""
+}
+```
+### category
+  Indicates (where applicable) the category of Entity identified by this LEI Data Record, as a more specific category within the broad definition given in ISO 17442. These categories are based on use cases specified in ROC policies, found at the ROC website.
+* **Type:** EntityCategory
+* **Example:**
+```
+{
+	"category": {}
+}
+```
+### crawlTimestamp
+  The default crawlTimestamp is the most recent date of all of the crawlTimestamps of the origins used to compute the Entity, returned as a UNIX time.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"crawlTimestamp": 1756796400
+}
+```
+### description
+  A few sentences describing an entity
+* **Type:** String
+* **Example:**
+```
+{
+	"description": ""
+}
+```
+### descriptors
+  A list of free-form keywords describing this entity
+* **Type:** String
+* **Example:**
+```
+{
+	"descriptors": ""
+}
+```
+### diffbotUri
+  diffbotUri is the URI an entity&#39;s  (URI), which is defined by appending the Diffbot ID to the URL https:&#x2F;&#x2F;diffbot.com&#x2F;entity&#x2F;. For example, Diffbot&#39;s entityID is CWSwJ_SWQPfqO3HQsxY4lGg and its DiffbotUri is https:&#x2F;&#x2F;diffbot.com&#x2F;entity&#x2F;CWSwJ_SWQPfqO3HQsxY4lGg
+* **Type:** URL
+* **Example:**
+```
+{
+	"diffbotUri": "http://diffbot.com/entity/Ed-KtAaRBO8G1urmPKsSE6g"
+}
+```
+### expirationReason
+  The reason that a Legal Entity ceased to operate. This element SHALL be present if EntityExpirationDate is present, and omitted otherwise.
+* **Type:** ExpirationReason
+* **Example:**
+```
+{
+	"expirationReason": {}
+}
+```
+### from
+   The date on which the legal entity was first established as defined in ISO 17442.
+* **Type:** DDate
+* **Example:**
+```
+{
+	"from": {
+		"str": "d2009-08-11",
+		"precision": 3,
+		"timestamp": 1249948800000
+	}
+}
+```
+### gleifId
+  The Legal Entity Identifier (LEI) is a 20-character, alpha-numeric code based on the ISO 17442 standard developed by the International Organization for Standardization (ISO)
+* **Type:** String
+* **Example:**
+```
+{
+	"gleifId": "54930070NSV60J38I987"
+}
+```
+### id
+  An alphanumeric string like CWSwJ_SWQPfqO3HQsxY4lGg that uniquely identifies an entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"id": "Ed-KtAaRBO8G1urmPKsSE6g"
+}
+```
+### image
+  The main image used to represent the entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"image": ""
+}
+```
+### images
+  The visual representation of an entity usually in the form of a png, jpeg, gif, or svg file.
+* **Type:** ImageField
+* **Example:**
+```
+{
+	"images": [
+		{
+			"classifications": "",
+			"fingerprint": "",
+			"title": "",
+			"isCached": false,
+			"url": ""
+		}
+	]
+}
+```
+### importance
+  A number between 0 and 100 indicating how important or popular an entity is.
+* **Type:** Float
+* **Example:**
+```
+{
+	"importance": 84.7000732421875
+}
+```
+### isCurrent
+  The status of Legal Entity.
+* **Type:** Boolean
+* **Example:**
+```
+{
+	"isCurrent": false
+}
+```
+### isinCodes
+  International Securities Identification Number (ISIN) is a 12-digit alphanumeric code that uniquely identifies a specific security.
+* **Type:** String
+* **Example:**
+```
+{
+	"isinCodes": ""
+}
+```
+### legalFormCode
+  The legal form of the Entity, taken from the ISO Entity Legal Form (ELF) code list maintained by GLEIF. The XML schema validates the format of EntityLegalFormCode codes but not the specific codes conforming to the ISO standard it requires.
+* **Type:** String
+* **Example:**
+```
+{
+	"legalFormCode": "XTIQ"
+}
+```
+### legalFormName
+  The legal form of the Entity, taken from the ISO Entity Legal Form (ELF) code list maintained by GLEIF. The XML schema validates the format of EntityLegalFormCode codes but not the specific codes conforming to the ISO standard it requires.
+* **Type:** String
+* **Example:**
+```
+{
+	"legalFormName": "Corporation"
+}
+```
+### legalJurisdiction
+  The jurisdiction of legal formation and registration of the Entity (and on which the Legalform data element is also dependent).
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"legalJurisdiction": {
+		"summary": "County in Pennsylvania, United States",
+		"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3Fav%40r%3ErO%3CLr2YkFhFl8D%7C8%5BoEd3MyKe%7BWyKY%3CVdba9Ds%3Bmv9KHdvZ0.Y%3AL",
+		"types": [
+			"Place",
+			"AdministrativeArea"
+		],
+		"name": "Delaware County",
+		"diffbotUri": "http://diffbot.com/entity/E7IuTriZ9PQO5_uSSzFb_eA",
+		"targetDiffbotId": "E7IuTriZ9PQO5_uSSzFb_eA",
+		"type": "Place"
+	}
+}
+```
+### location
+  The main&#x2F;headquarters location of the entity.
+* **Type:** Location
+* **Example:**
+```
+{
+	"location": {
+		"country": {
+			"summary": "Country located primarily in North America",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ",
+			"types": [
+				"Place",
+				"AdministrativeArea",
+				"Country"
+			],
+			"name": "United States",
+			"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
+			"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
+			"type": "Place"
+		},
+		"address": "251 Little Falls Drive, Wilmington, North Carolina",
+		"city": {
+			"summary": "County seat city in New Hanover County, North Carolina, United States",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGt%3E%7CW8Zl%3Aa%3FPh%2CX%5DGxKUewf%3DS%7ELgs.%7BGW",
+			"types": [
+				"Place",
+				"AdministrativeArea",
+				"City"
+			],
+			"name": "Wilmington",
+			"diffbotUri": "http://diffbot.com/entity/EPXZO2D_wOPe5Gmax4CCHhg",
+			"targetDiffbotId": "EPXZO2D_wOPe5Gmax4CCHhg",
+			"type": "Place"
+		},
+		"street": "251 Little Falls Drive",
+		"subregion": {
+			"summary": "County in North Carolina, United States",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEw%3ErO%3CLr2YiPlLankgI%5CrMs%7CCzL%60z%5Cz%3EXBXs5%5BkHs9CrHwOTzEJ%3C%5B2Yt.e9%40",
+			"types": [
+				"Place",
+				"AdministrativeArea"
+			],
+			"name": "New Hanover County",
+			"diffbotUri": "http://diffbot.com/entity/EpyBwArEBNfqFiqZI0_ggGw",
+			"targetDiffbotId": "EpyBwArEBNfqFiqZI0_ggGw",
+			"type": "Place"
+		},
+		"latitude": 34.209197998046875,
+		"precision": 11.717340469360352,
+		"postalCode": "19808",
+		"locationType": [
+			"Headquarters"
+		],
+		"region": {
+			"summary": "State of the United States of America",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FCvrP%3EkZ%7DTb%3B%60z%2FiJmw7I8_uPn9E.Voy",
+			"types": [
+				"Place",
+				"AdministrativeArea",
+				"Region"
+			],
+			"name": "North Carolina",
+			"diffbotUri": "http://diffbot.com/entity/E0i5G2lPGOk-eosDVCXvOpw",
+			"targetDiffbotId": "E0i5G2lPGOk-eosDVCXvOpw",
+			"type": "Place"
+		},
+		"longitude": -77.87191009521484
+	}
+}
+```
+### locations
+  The locations of the entity.
+* **Type:** Location
+* **Example:**
+```
+{
+	"locations": [
+		{
+			"venue": "Service Company",
+			"country": {
+				"summary": "Country located primarily in North America",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ",
+				"types": [
+					"Place",
+					"AdministrativeArea",
+					"Country"
+				],
+				"name": "United States",
+				"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
+				"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
+				"type": "Place"
+			},
+			"address": "Service Company, 251 C/O Corporation Little Falls Drive, Wilmington, North Carolina",
+			"city": {
+				"summary": "County seat city in New Hanover County, North Carolina, United States",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGt%3E%7CW8Zl%3Aa%3FPh%2CX%5DGxKUewf%3DS%7ELgs.%7BGW",
+				"types": [
+					"Place",
+					"AdministrativeArea",
+					"City"
+				],
+				"name": "Wilmington",
+				"diffbotUri": "http://diffbot.com/entity/EPXZO2D_wOPe5Gmax4CCHhg",
+				"targetDiffbotId": "EPXZO2D_wOPe5Gmax4CCHhg",
+				"type": "Place"
+			},
+			"street": "251 C/O Corporation Little Falls Drive",
+			"subregion": {
+				"summary": "County in North Carolina, United States",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEw%3ErO%3CLr2YiPlLankgI%5CrMs%7CCzL%60z%5Cz%3EXBXs5%5BkHs9CrHwOTzEJ%3C%5B2Yt.e9%40",
+				"types": [
+					"Place",
+					"AdministrativeArea"
+				],
+				"name": "New Hanover County",
+				"diffbotUri": "http://diffbot.com/entity/EpyBwArEBNfqFiqZI0_ggGw",
+				"targetDiffbotId": "EpyBwArEBNfqFiqZI0_ggGw",
+				"type": "Place"
+			},
+			"latitude": 34.209197998046875,
+			"precision": 11.717340469360352,
+			"postalCode": "19808",
+			"locationType": [
+				"Legal"
+			],
+			"region": {
+				"summary": "State of the United States of America",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FCvrP%3EkZ%7DTb%3B%60z%2FiJmw7I8_uPn9E.Voy",
+				"types": [
+					"Place",
+					"AdministrativeArea",
+					"Region"
+				],
+				"name": "North Carolina",
+				"diffbotUri": "http://diffbot.com/entity/E0i5G2lPGOk-eosDVCXvOpw",
+				"targetDiffbotId": "E0i5G2lPGOk-eosDVCXvOpw",
+				"type": "Place"
+			},
+			"longitude": -77.87191009521484
+		}
+	]
+}
+```
+### micCodes
+  Market identifier code (MIC) is an international indicator that identifies stock markets and trading exchanges for trading computers.
+* **Type:** String
+* **Example:**
+```
+{
+	"micCodes": ""
+}
+```
+### name
+  Primary text label for this entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"name": "GENERAL MOTORS COMPANY"
+}
+```
+### nbIncomingEdges
+  This is the number of edges in the Knowledge Graph that point to this entity. For example, the nbIncomingEdges field for Google is over 100,000. This number includes the number of people that work at google, the number of investors who invested in google, etc.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"nbIncomingEdges": 307
+}
+```
+### nbOrigins
+  Total number of origins in the field &#39;origins&#39;. This field is only available in extended JSON mode.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"nbOrigins": 1
+}
+```
+### nonCanonicalFacts
+  Enumerates all the non-canonical fields (i.e., those not defined in the ontology) that have a value for this entity. For instance, if &#39;numberOfChildren&#39; is listed in &#39;nonCanonicalFacts&#39; then the entity JSON will have the key &#39;numberOfChildren&#39; with an associated value. This field is only provided when the parameter nonCanonicalFacts&#x3D;1 is set. See: https:&#x2F;&#x2F;docs.diffbot.com&#x2F;kgapi
+* **Type:** String
+* **Example:**
+```
+{
+	"nonCanonicalFacts": ""
+}
+```
+### originDetails
+  Additional information about origins listed in &#39;origins&#39;, including the latest time it was crawled. This field is only available in extended JSON mode.
+* **Type:** OriginDetail
+* **Example:**
+```
+{
+	"originDetails": [
+		{
+			"crawledAt": {
+				"str": "",
+				"precision": 0,
+				"timestamp": 0
+			},
+			"origin": ""
+		}
+	]
+}
+```
+### origins
+  An origin is a web address where Diffbot found one or more facts about an entity. This field is only available in extended JSON mode.
+* **Type:** String
+* **Example:**
+```
+{
+	"origins": [
+		"gleif.org/54930070NSV60J38I987"
+	]
+}
+```
+### parent
+  The parent company of this subsidiary.
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"parent": [
+		{
+			"summary": "",
+			"image": "",
+			"images": [
+				{
+					"classifications": "",
+					"fingerprint": "",
+					"title": "",
+					"isCached": false,
+					"url": ""
+				}
+			],
+			"types": "",
+			"diffbotUri": "",
+			"name": ""
+		}
+	]
+}
+```
+### registerName
+  The name of the register
+* **Type:** String
+* **Example:**
+```
+{
+	"registerName": ""
+}
+```
+### registrationAuthority
+  The registration authority
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"registrationAuthority": {
+		"name": "Division of Corporations, Department of State",
+		"type": "Organization"
+	}
+}
+```
+### relationships
+  The list of relationships from this legal entity to other legal entities
+* **Type:** LegalEntityRelationship
+* **Example:**
+```
+{
+	"relationships": [
+		{
+			"relationshipPeriod": "",
+			"isCurrent": false,
+			"relationshipType": "",
+			"relatedEntity": {
+				"summary": "",
+				"image": "",
+				"images": [
+					{
+						"classifications": "",
+						"fingerprint": "",
+						"title": "",
+						"isCached": false,
+						"url": ""
+					}
+				],
+				"types": "",
+				"diffbotUri": "",
+				"name": ""
+			},
+			"from": {
+				"str": "",
+				"precision": 0,
+				"timestamp": 0
+			}
+		}
+	]
+}
+```
+### subCategory
+  Indicates and specifies further (where applicable) the sub-category (sub-sector) of Legal Entity identified by this LEI Record and already categorized by the EntityCategory.
+* **Type:** EntitySubCategory
+* **Example:**
+```
+{
+	"subCategory": {}
+}
+```
+### subsidiaries
+  Current subsidiaries of this organization.
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"subsidiaries": [
+		{
+			"types": [
+				"LegalEntity"
+			],
+			"name": "GMF Prime Automobile Trust 2023-PP2",
+			"diffbotUri": "http://diffbot.com/entity/E02M9Q4msMXawz8hLc-QVeA",
+			"targetDiffbotId": "E02M9Q4msMXawz8hLc-QVeA",
+			"type": "LegalEntity"
+		},
+		{
+			"types": [
+				"LegalEntity"
+			],
+			"name": "GM FINANCIAL AUTOMOBILE LEASING TRUST 2022-1",
+			"diffbotUri": "http://diffbot.com/entity/E7-Egb5iSPpqa54ZY0BjFrg",
+			"targetDiffbotId": "E7-Egb5iSPpqa54ZY0BjFrg",
+			"type": "LegalEntity"
+		},
+		{
+			"types": [
+				"LegalEntity"
+			],
+			"name": "GM Financial Automobile Leasing Trust 2021-PP4",
+			"diffbotUri": "http://diffbot.com/entity/EB0UAYra1NjCEXcnNHAJ8Sg",
+			"targetDiffbotId": "EB0UAYra1NjCEXcnNHAJ8Sg",
+			"type": "LegalEntity"
+		}
+	]
+}
+```
+### successorEntity
+  The surviving&#x2F;new Legal Entity which continues&#x2F;replaces this LEI registration, where applicable.
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"successorEntity": {
+		"summary": "",
+		"image": "",
+		"images": [
+			{
+				"classifications": "",
+				"fingerprint": "",
+				"title": "",
+				"isCached": false,
+				"url": ""
+			}
+		],
+		"types": "",
+		"diffbotUri": "",
+		"name": ""
+	}
+}
+```
+### summary
+  A short phrase designed to disambiguate entities with the same or similar name
+* **Type:** String
+* **Example:**
+```
+{
+	"summary": ""
+}
+```
+### to
+  The date the Legal Entity ceased operation or was merged. This element SHALL be present if EntityExpirationReason is present, and omitted otherwise.
+* **Type:** DDate
+* **Example:**
+```
+{
+	"to": {
+		"str": "",
+		"precision": 0,
+		"timestamp": 0
+	}
+}
+```
+### type
+  The top-level type of a Diffbot entity. Examples of type include Person, Organization, Article, Product.
+* **Type:** Type
+* **Example:**
+```
+{
+	"type": "LegalEntity"
+}
+```
+### types
+  All types of a Diffbot entity, including the value of the field &#39;type&#39;.
+* **Type:** String
+* **Example:**
+```
+{
+	"types": [
+		"LegalEntity"
+	]
+}
+```
+### ultimateParent
+  The ultimate parent company of this subsidiary.
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"ultimateParent": [
+		{
+			"summary": "",
+			"image": "",
+			"images": [
+				{
+					"classifications": "",
+					"fingerprint": "",
+					"title": "",
+					"isCached": false,
+					"url": ""
+				}
+			],
+			"types": "",
+			"diffbotUri": "",
+			"name": ""
+		}
+	]
+}
+```
+### wikipediaPageviews
+  The number of views of its Wikipedia page of the last month if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviews": 0
+}
+```
+### wikipediaPageviewsGrowth
+  The month over month growth of wikipediaPageviews, where we count the increment of the number of page views of the second to last (full) month, compared with that of the last (full) month. if today was Aug 16th, 2022, the last complete month is July. So it refers to the increment from June to July, i.e., ( f(July) - f(June) ) ÷ f(June) x 100%. The f(.) only counts the first 28 days of a month, to avoid fluctuations between 31-days months like Jan and 28(29)-days months like Feb.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsGrowth": ""
+}
+```
+### wikipediaPageviewsLastQuarter
+  The number of views of its Wikipedia page of the last quarter if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastQuarter": 0
+}
+```
+### wikipediaPageviewsLastQuarterGrowth
+  The quarter over quarter growth of wikipediaPageviews, where we count the increment of the number of page views of the second to last (full) quarter, compared with that of the last (full) quarter. If today was Aug 16th, 2022, the last complete quarter is Q2 (April, May, June). So it refers to the increment from Q1 to Q2, i.e., ( f(Q2) - f(Q1) ) ÷ f(Q1) x 100%.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastQuarterGrowth": ""
+}
+```
+### wikipediaPageviewsLastYear
+  The number of views of its Wikipedia page of the last year if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastYear": 0
+}
+```
+### wikipediaPageviewsLastYearGrowth
+  The year over year growth of wikipediaPageviews, where we count the monthly-rolling increment of the year before last than the last year. It today was Aug 16th, 2022, it is computed by comparing the numbers from Aug 2021 to July 2022 and from Aug 2020 to July 2021, i.e., ( f(Aug 2021 to July 2022) - f(Aug 2020 to July 2021) ) ÷ f(Aug 2020 to July 2021) x 100%.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastYearGrowth": ""
+}
+```
diff --git a/docs/kg-ont-administrativearea.md b/docs/kg-ont-administrativearea.md
index 05f0606f..c846f3fd 100644
--- a/docs/kg-ont-administrativearea.md
+++ b/docs/kg-ont-administrativearea.md
@@ -1,42 +1,27 @@
 ---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
 id: kg-ont-administrativearea
 title: AdministrativeArea
+generatedBy: generateOntology.js
 ---
 
-The Administrative Area entity type encompasses all cities, regions, counties, sub-regions, provinces, and countries known to the Knowledge Graph. 
+A sub-type of [Place](doc:place), the Administrative Area entity type encompasses all cities, regions, counties, sub-regions, provinces, and countries known to the Knowledge Graph. 
 
 Note that fields are not guaranteed to exist in every entity record.
 
->New to the Diffbot Knowledge Graph? [Start here](dql-quickstart).
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
 
 ## AdministrativeArea Fields
-* [area](#area) 
-* [areaCodes](#areacodes) 
 * [geonameId](#geonameid) 
-* [population](#population) 
-* [postalCodes](#postalcodes) 
 
 ## AdministrativeArea Field Details
 Note that certain longer field examples may be truncated for readability.
 
-### area
-  Square kilometers of AdministrativeArea
-* **Type:** Integer
-* **Example:**
-```
-{
-	"area": 423970
-}
-```
-### areaCodes
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"areaCodes": ""
-}
-```
 ### geonameId
   
 * **Type:** Integer
@@ -46,21 +31,3 @@ Note that certain longer field examples may be truncated for readability.
 	"geonameId": 0
 }
 ```
-### population
-  
-* **Type:** Integer
-* **Example:**
-```
-{
-	"population": 39144818
-}
-```
-### postalCodes
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"postalCodes": ""
-}
-```
diff --git a/docs/kg-ont-article.md b/docs/kg-ont-article.md
index 39e4d85c..ff941bcb 100644
--- a/docs/kg-ont-article.md
+++ b/docs/kg-ont-article.md
@@ -1,36 +1,51 @@
 ---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
 id: kg-ont-article
 title: Article
+generatedBy: generateOntology.js
 ---
 
 The article entity type encompasses news, blog posts, and article content known to the Knowledge Graph. 
 
 Note that fields are not guaranteed to exist in every entity record.
 
->New to the Diffbot Knowledge Graph? [Start here](dql-quickstart).
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
 
 ## Article Fields
 * [author](#author) 
 * [authorUrl](#authorurl) 
 * [breadcrumb](#breadcrumb) 
+* [categories](#categories) 
+* [crawlTimestamp](#crawltimestamp) 
 * [date](#date) 
+* [diffbotUri](#diffboturi) 
 * [discussion](#discussion) 
 * [estimatedDate](#estimateddate) 
 * [html](#html) 
 * [icon](#icon) 
+* [id](#id) 
 * [images](#images) 
 * [language](#language) 
 * [nextPage](#nextpage) 
 * [nextPages](#nextpages) 
 * [numPages](#numpages) 
+* [pageUrl](#pageurl) 
 * [publisherCountry](#publishercountry) 
 * [publisherRegion](#publisherregion) 
 * [quotes](#quotes) 
+* [resolvedPageUrl](#resolvedpageurl) 
 * [sentiment](#sentiment) 
 * [siteName](#sitename) 
 * [tags](#tags) 
 * [text](#text) 
 * [title](#title) 
+* [type](#type) 
+* [types](#types) 
 * [videos](#videos) 
 
 ## Article Field Details
@@ -51,7 +66,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"authorUrl": "https://www.zdnet.com/meet-the-team/us/george-anadiotis/"
+	"authorUrl": "https://www.zdnet.com/meet-the-team/george-anadiotis/"
 }
 ```
 ### breadcrumb
@@ -62,12 +77,44 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"breadcrumb": [
 		{
-			"link": "",
-			"name": ""
+			"link": "https://www.zdnet.com/",
+			"name": "Home"
+		},
+		{
+			"link": "https://www.zdnet.com/topic/business/",
+			"name": "Business"
+		},
+		{
+			"link": "https://www.zdnet.com/topic/data-management/",
+			"name": "Data Management"
 		}
 	]
 }
 ```
+### categories
+  
+* **Type:** ArticleCategory
+* **Example:**
+```
+{
+	"categories": [
+		{
+			"score": 0.837,
+			"name": "Technology & Computing",
+			"id": "iabv2-596"
+		}
+	]
+}
+```
+### crawlTimestamp
+  Last time a site was crawled&#x2F;indexed
+* **Type:** Integer
+* **Example:**
+```
+{
+	"crawlTimestamp": 1684016661
+}
+```
 ### date
   
 * **Type:** DDateTime
@@ -81,6 +128,15 @@ Note that certain longer field examples may be truncated for readability.
 	}
 }
 ```
+### diffbotUri
+  diffbotUri is a combination of an entityID and a corresponding web address or uniform resource identifier (URI), which is defined by appending the entityID to the URL https:&#x2F;&#x2F;www.diffbot.com&#x2F;entity&#x2F;. For example, Diffbot&#39;s entityID is CWSwJ_SWQPfqO3HQsxY4lGg and its DiffbotUri is https:&#x2F;&#x2F;www.diffbot.com&#x2F;entity&#x2F;CWSwJ_SWQPfqO3HQsxY4lGg
+* **Type:** String
+* **Example:**
+```
+{
+	"diffbotUri": "http://diffbot.com/entity/ART96037639621"
+}
+```
 ### discussion
   
 * **Type:** GIDiscussionField
@@ -141,7 +197,6 @@ Note that certain longer field examples may be truncated for readability.
 				"text": ""
 			}
 		],
-		"numParticipants": 0,
 		"tags": [
 			{
 				"score": "",
@@ -152,6 +207,7 @@ Note that certain longer field examples may be truncated for readability.
 				"uri": ""
 			}
 		],
+		"numParticipants": 0,
 		"rssUrl": ""
 	}
 }
@@ -163,9 +219,9 @@ Note that certain longer field examples may be truncated for readability.
 ```
 {
 	"estimatedDate": {
-		"str": "d2018-08-30T14:09:17",
+		"str": "d2018-08-30T00:00",
 		"precision": 4,
-		"timestamp": 1535638157000
+		"timestamp": 1535587200000
 	}
 }
 ```
@@ -175,7 +231,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"html": "<p><a href=\"https://www.zdnet.com/pictures/a-basic-guide-to-the-deep-dark-web/\">The web</a> is among humankind's greatest achievements and resources. Ever-expanding and nearly all-encompassing, we've all come to depend on it. There's just one problem: It takes work to get information out of it.</p>\n<p>That's because the <a href=\"https://www.zdnet.com/article/hackers-target-security-researchers-with-malware-laden-document/\">information is in documents</a>, and documents on the web are all over the place, and someone needs to locate them, and read them, to extract that information. Search engines have come a long way, and they greatly assist in the locating part, but not so much in the extracting part. At least, not until today.</p>\n<p><strong>Also: <a href=\"https://www.zdnet.com/article/zen-and-the-art-of-data-structures-from-self-tuning-to-self-designing-data-systems/\">Zen and the art of data structures: From self-tuning to self-designing data systems</a></strong></p>\n<p>Google and its ilk may sometimes give the impression they can understand and answer questions. Part of the reason is the addition of human knowledge in the mix. Google famously went from using purely text-based and statistical methods to adding a form of curation when it bought <a href=\"https://www.zdnet.com/article/google-says-it-wont-build-ai-for-weapons/\">MetaWeb</a>. MetaWeb developed Freebase, which was a crowd-sourced knowledge graph, similar in approach to Wikipedia, which was integrated in Google's search engine.</p>\n<h2>Eat your heart out, Google</h2>\n<p>That enables Google to do some of its magic. If you Google &quot;<a href=\"https://www.google.com/search?q=Google&rlz=1CAZZAF_enUS792US792&oq=Google&aqs=chrome..69i57j69i60l3j69i65j69i60.381j0j9&sourceid=chrome&ie=UTF-8\">Google</a>,&quot; for example, you don't just get a bunch of links. You also get an info-box that lists facts such as Google's CEO, founders, and address. That's because there is an entry in Google's knowledge graph that lists Google as a company, and these are some of the properties companies have, so Google fetches and displays that information from Wikipedia.</p>\n<p>But if you try Googling &quot;how many employees does Google have,&quot; or &quot;what is Google's address&quot;, what you will get is a bunch of links. You are on your own -- you have to read the documents and figure out the answer. If that information was in a database, you would type something like &quot;<em>SELECT Address FROM Organizations WHERE Name=Google</em>&quot; and you'd have your answer in seconds. That is the difference between structured and unstructured information.</p>\n<p><strong>Also: <a href=\"https://www.zdnet.com/article/memsql-6-5-newsql-with-autonomous-workload-optimization-improved-data-ingestion-and-query-execution/\">MemSQL 6.5: NewSQL with autonomous workload optimization, improved data ingestion and query execution speed</a></strong></p>\n<p>That is also what <a href=\"https://www.diffbot.com/\">Diffbot</a> is unveiling today: The ability to query the web as a database. This impressive feat is also based on a knowledge graph. The difference is that, in Diffbot's case, the knowledge graph is only partially curated by humans, and is automatically populated by crawling the web. <em>ZDNet </em>talked to Mike Tung, Diffbot's CEO and Founder, to find out how Diffbot does this.</p>\n<figure><img alt=\"opera-snapshot2018-08-30101415www-diffbot-com.png\" src=\"https://zdnet2.cbsistatic.com/hub/i/r/2018/08/30/ad927664-7ba0-4352-a3d7-6c3efdd8a18d/resize/470xauto/466e3fcf32bac06b562faa1ae8637f74/opera-snapshot2018-08-30101415www-diffbot-com.png\"></img><figcaption>Diffbot ingests and parses the entire web into a knowledge graph - a database you can query. Image: Diffbot</figcaption></figure>\n<p>First off, you have to crawl the web. This is where <a href=\"https://www.gigablast.com/about.html\">Gigablast</a> and Matt Wells come in. Gigablast is a search engine created by Matt Wells, Diffbot's VP of Search, in 2000. Tung says this is what Diffbot uses to crawl, and store, every single document on the web. Hard as this may be, however, it's not even half the job.</p>\n<p>The really hard part is getting the information out of documents, and this is where the magic is. Tung explains this is done using computer vision, machine learning (ML), and natural language processing (NLP).</p>\n<p>Computer vision helps <a href=\"https://www.diffbot.com/\">Diffbot</a> understand the structure of documents. It mimics the way humans break down documents, figuring out what are the structural elements of each document -- things such as headers, blocks, etc. In a perfect world, this should be possible by inspecting the HTML structure of web documents. But not everything on the web is HTML, and HTML documents are not perfect either.</p>\n<p><strong>Also: <a href=\"https://www.zdnet.com/article/memsql-6-5-newsql-with-autonomous-workload-optimization-improved-data-ingestion-and-query-execution/\">MemSQL 6.5: NewSQL with autonomous workload optimization, improved data ingestion and query execution speed</a></strong></p>\n<p>After structure comes content. Content is parsed using a combination of NLP and ML, the result of which is structured knowledge which is added to <a href=\"https://www.diffbot.com/knowledge-graph\">Diffbot's knowledge graph</a> (DKG). Tung showcased an example based on Marissa Mayer, ex-CEO of Yahoo.</p>\n<p>Taking a brief text about Mayer as input, Diffbot's system processed it and was able to extract all kinds of facts described in the text: Mayer's gender, employment history, education, etc. By doing this, Diffbot adds an entry for Mayer in its knowledge graph, and populates it with properties such as gender, age, and the like.</p>\n<p>&quot;Contrary to popular perception, <a href=\"https://searchengineland.com/google-builds-next-gen-knowledge-graph-future-201640\">Google's knowledge graph is not derived primarily from automation</a>,&quot; says Tung. &quot;Unlike Google, the goal of our processing is not to rank pages for humans to read (and inject some advertising along the way), but rather to avoid human reading altogether.</p>\n<p>DKG is the first web-scale knowledge graph that is entirely synthesized by an <a href=\"https://www.zdnet.com/article/five-tech-jobs-that-ai-and-automation-will-make-radically-more-efficient/\">automated AI system</a>, without a human-in-the-loop. That is why the main constraint to growth is the number of machines that we dedicate to it acquiring knowledge,&quot; he adds, concluding that DKG currently contains something in the area of one billion facts.</p>\n<h2>From a web of documents to a web of data</h2>\n<p>This is not entirely new. The first one who put forward the vision of going from a web of documents to a web of data was none other than the web's inventor, <a href=\"https://www-sop.inria.fr/acacia/fabien/lecture/licence_travaux_etude2002/TheSemanticWeb/\">Tim Berners Lee, who published his Semantic Web manifesto in 2001</a>.</p>\n<p>As Tung notes, however, &quot;a long line of history (ranging from RDF/microformats/RSS/semantic markup) has shown that requiring human annotation is never going to scale in terms of economic incentive and accuracy to all of knowledge.&quot;</p>\n<p>Even though annotation does not necessarily have to be human (it can come from automation as well), Tung does have a point: Most content on the web is very poorly, if at all, annotated. Tung thinks that building this global knowledge graph using the current state of AI is the right approach -- and it seems to be working.</p>\n<p><strong>Also: <a href=\"https://www.zdnet.com/article/moving-fast-without-breaking-data-governance-for-managing-risk-in-machine-learning-and-beyond/\">Moving fast without breaking data: Governance for managing risk in machine learning and beyond</a></strong></p>\n<p>The applications are wide and far-reaching. Tung notes that &quot;enterprise functions such as sales, recruiting, supply chain, accounting, business intelligence and market intelligence all work off of databases that can be kept updated and accurate by integrating directly with the knowledge graph.&quot;</p>\n<figure><img alt=\"diffbot-kg-record-linking.jpg\" data-original=\"    https://zdnet3.cbsistatic.com/hub/i/r/2018/08/30/79b11205-86a0-4b60-ad1a-658a49e3bcc1/resize/470xauto/287cba267d3c5cbb262778944f9d1eb3/diffbot-kg-record-linking.jpg\" src=\"https://zdnet3.cbsistatic.com/hub/i/r/2018/08/30/79b11205-86a0-4b60-ad1a-658a49e3bcc1/resize/470xauto/287cba267d3c5cbb262778944f9d1eb3/diffbot-kg-record-linking.jpg\"></img><figcaption>Diffbot natural language processing in action. Note how facts extracted from text are represented as subject -- predicate -- object triples. (Image: Diffbot)</figcaption></figure>\n<p>Tung demonstrated such a scenario, using DKG to query for people who work for Uber. Initially the query returned nearly 40,000 results, which Tung was able to filter using standard filtering as one would expect from a <a href=\"https://www.zdnet.com/article/the-new-era-of-the-multi-model-database/\">database</a>: Get only current employees, filter by region, etc.</p>\n<p>And that reference to integrating with databases has far-reaching implications too. The above scenario was based only on information found on the web. But enterprises don't just work with what they find on the web -- they also have their own internal systems and databases, and Tung says DKG can support those as well, offering one access point to rule them all.</p>\n<p><strong>Also: <a href=\"https://www.zdnet.com/article/graphql-for-databases-a-layer-for-universal-database-access/\">GraphQL for databases: A layer for universal database access?</a></strong></p>\n<p>DKG may well count as Diffbot's greatest achievement to date, but it did not come out of nowhere. Tung has strong credentials to show for, having designed web-scale information extraction architectures and worked for <a href=\"https://www.zdnet.com/topic/microsoft/\">Microsoft</a>, eBay, and Yahoo. Diffbot has been around since 2008, it has names such as eBay Microsoft Bing, and Salesforce among its clients, and Tencent and Bloomberg among its investors.</p>\n<p>Impressive as all of that may sound, however, there are a few gotchas.</p>\n<h2>Language, son</h2>\n<p>To begin with, not all of DKG is auto-magically created. That's not necessarily a bad thing, but it goes to show the limits of even what &quot;the current state of AI&quot; can do. DKG is seeded by Diffbot's knowledge engineers, who have decided that the entities it will handle are people, companies, locations, articles, products, discussions, and images.</p>\n<p>This means that everything Diffbot <a href=\"https://www.zdnet.com/article/robot-will-crawl-through-pipes-to-help-decommission-nuclear-facility/\">crawls</a> from the web will be classified as one of those things. Clearly, this decision was driven by what Diffbot's clients are mostly interested in, but that does not mean every page on the web is classified as one of the 20 types DKG currently knows. Tung says they plan to expand this to include categories such as events or medical information.</p>\n<p>In other words, Diffbot has consciously chosen to limit the scope of what it handles, to make a well-known problem manageable. To anyone familiar with <a href=\"http://connected-data.london/2018/06/11/building-enterprise-knowledge-graphs-in-the-real-world/\">knowledge graphs (also going by the name of ontologies for the connaisseurs</a>), what Diffbot does is defining an upper ontology, and populating it from the web. The concept and related challenges are well-known, but the way Diffbot handles this is state of the art.</p>\n<p><strong>Also: <a href=\"https://www.zdnet.com/article/aws-neptune-going-ga-the-good-the-bad-and-the-ugly-for-graph-database-users-and-vendors/\">AWS Neptune going GA: The good, the bad, and the ugly for graph database users and vendors</a></strong></p>\n<p>Which bring us to another key topic: Question answering. If you have the whole web at your fingertips, how are you going to query it? It depends. If you are a business person, ideally, you would like to use natural language. At present, DKG does not support this. It does, however, have its own Diffbot Query Language (DQL).</p>\n<p>DQL looks pretty simple, if you are familiar with query languages. But, then again, if you are familiar with query languages, why would you want to have to learn yet another one? There already is bunch of <a href=\"https://www.zdnet.com/article/back-to-the-future-does-graph-database-success-hang-on-query-language/\">graph query languages</a> out there, such as SPARQL, Gremlin, and OpenCypher, and with the <a href=\"https://www.zdnet.com/article/the-rise-and-rise-of-graph-databases/\">rise of graph databases</a>, we expect them to become more and more widespread.</p>\n<p>This touches upon another issue: Even though Diffbot's approach shares many similarities with semantic web concepts and standards (Tung even specifically mentioned <a href=\"https://www.zdnet.com/article/nba-analytics-and-rdf-graphs-game-data-and-metadata-evolution-and-occams-razor/\">RDF-like subject-predicate-object triples</a> in his breakdown of text processing), its approach is proprietary.</p>\n<p>Regardless of whether you know or like those standards, would it not have made Diffbot's life easier to use them? For example, by building DKG on top of an off-the-shelf graph database. Tung acknowledges it would, but he says they tested over a dozen <a href=\"http://yearofthegraph.xyz\">graph databases</a>, and they all broke down at around 10-100M entities, so they had to build something proprietary.</p>\n<p>As for the language issue, Tung says their approach is to meet users where they are, eliminating the need for directly using a query language (or an API, which DKG also supports) as much as possible. The way to do this, Tung says, is by integrating DKG with popular systems such as Salesforce, SAP, or Tableau, so users can transparently get data from DKG in their applications.</p>\n<p>That may be good for users, but it also places quite a burden of Diffbot to develop and maintain all those integrations. Tung says they intend to develop bridges for popular query languages, however, so integrations will not have to be hand-crafted.</p>\n<p><strong>Also: <a href=\"https://www.zdnet.com/article/planet-analytics-1-0-from-the-lab-to-production/\">Planet analytics 1.0: From the UN lab to the globe</a></strong></p>\n<p>Last but not least, does being able to query the web also mean you should automatically trust the results? Not necessarily. This is why Google and its ilk have developed sophisticated algorithms to rank results, trying to determine the most relevant ones. DKG only partially does this.</p>\n<p>You can filter Uber employees by age, for example, but what is the definitive source for that? If source X says a person was born in 1974, and source Y says they were born in 1947, which one should you trust? How do you know they are talking about the same person to begin with?</p>\n<p>These are well-known, hard-to-tackle issues, and Diffbot has to tackle them like anyone else who has come before them. Even as it is, however, DKG is an impressive achievement with many potential applications.</p>\n<p><a href=\"https://www.zdnet.com/article/ai-chips-for-big-data-and-machine-learning-gpus-fpgas-and-hard-choices-in-the-cloud-and-on-premise/\"><strong>AI chips for big data and machine learning: GPUs, FPGAs, and hard choices in the cloud and on-premise</strong></a></p>\n<p>How can GPUs and FPGAs help with data-intensive tasks such as operations, analytics, and machine learning, and what are the options?</p>\n<p>With natural disasters picking up in frequency and intensity, the role of NGOs in disaster relief is picking up as well. A key requirement for all NGOs is transparency, and applying data-driven techniques may help.</p>\n<p>Wolfram, having been into AI before it was cool, now gets a piece of the deep learning hype, in its sui generis way. Where does it stand compared to the competition, and how easy is it to use and integrate Wolfram with the rest of the world?</p>"
+	"html": "<figure><picture> <img alt=\"59ef6a2260b25a01359a7201-1280x7201nov032017164306poster.jpg\" src=\"https://www.zdnet.com/a/img/resize/28753f7b6fe517051d38dfa7436268bc9ad26753/2017/11/03/39e92e2e-027b-46b5-b15a-11f3844919a9/59ef6a2260b25a01359a7201-1280x7201nov032017164306poster.jpg?auto=webp&fit=crop&frame=1&height=814.5&width=1449\"></img></picture></figure>\n<p><a href=\"https://www.zdnet.com/pictures/a-basic-guide-to-the-deep-dark-web/\">The web</a> is among humankind's greatest achievements and resources. Ever-expanding and nearly all-encompassing, we've all come to depend on it. There's just one problem: It takes work to get information out of it.</p>\n<h3>Featured</h3>\n<ul><li><a href=\"https://www.zdnet.com/article/i-asked-chatgpt-bing-and-bard-what-worries-them-googles-ai-went-terminator-on-me/\"> I asked ChatGPT, Bing, and Bard what worries them. Google's AI went Terminator on me </a></li><li><a href=\"https://www.zdnet.com/article/eight-habits-of-highly-secure-remote-workers/\"> 8 habits of highly-secure remote workers </a></li><li><a href=\"https://www.zdnet.com/article/this-tiny-satellite-communicator-is-packed-full-of-features-and-peace-of-mind/\"> This tiny satellite communicator is packed full of features and peace of mind </a></li><li><a href=\"https://www.zdnet.com/article/best-android-smartwatch/\"> The best Android smartwatches (and which ones can function without a phone) </a></li></ul>\n<p>That's because the <a href=\"https://www.zdnet.com/article/hackers-target-security-researchers-with-malware-laden-document/\">information is in documents</a>, and documents on the web are all over the place, and someone needs to locate them, and read them, to extract that information. Search engines have come a long way, and they greatly assist in the locating part, but not so much in the extracting part. At least, not until today.</p>\n<p><strong>Also: <a href=\"https://www.zdnet.com/article/zen-and-the-art-of-data-structures-from-self-tuning-to-self-designing-data-systems/\">Zen and the art of data structures: From self-tuning to self-designing data systems</a></strong></p>\n<p>Google and its ilk may sometimes give the impression they can understand and answer questions. Part of the reason is the addition of human knowledge in the mix. Google famously went from using purely text-based and statistical methods to adding a form of curation when it bought <a href=\"https://www.zdnet.com/article/google-says-it-wont-build-ai-for-weapons/\">MetaWeb</a>. MetaWeb developed Freebase, which was a crowd-sourced knowledge graph, similar in approach to Wikipedia, which was integrated in Google's search engine.</p>\n<h2>Eat your heart out, Google</h2>\n<p>That enables Google to do some of its magic. If you Google &quot;<a href=\"https://www.google.com/search?q=Google&rlz=1CAZZAF_enUS792US792&oq=Google&aqs=chrome..69i57j69i60l3j69i65j69i60.381j0j9&sourceid=chrome&ie=UTF-8\">Google</a>,&quot; for example, you don't just get a bunch of links. You also get an info-box that lists facts such as Google's CEO, founders, and address. That's because there is an entry in Google's knowledge graph that lists Google as a company, and these are some of the properties companies have, so Google fetches and displays that information from Wikipedia.</p>\n<p>But if you try Googling &quot;how many employees does Google have,&quot; or &quot;what is Google's address&quot;, what you will get is a bunch of links. You are on your own -- you have to read the documents and figure out the answer. If that information was in a database, you would type something like &quot;<em>SELECT Address FROM Organizations WHERE Name=Google</em>&quot; and you'd have your answer in seconds. That is the difference between structured and unstructured information.</p>\n<p><strong>Also: <a href=\"https://www.zdnet.com/article/memsql-6-5-newsql-with-autonomous-workload-optimization-improved-data-ingestion-and-query-execution/\">MemSQL 6.5: NewSQL with autonomous workload optimization, improved data ingestion and query execution speed</a></strong></p>\n<p>That is also what <a href=\"https://www.diffbot.com/\">Diffbot</a> is unveiling today: The ability to query the web as a database. This impressive feat is also based on a knowledge graph. The difference is that, in Diffbot's case, the knowledge graph is only partially curated by humans, and is automatically populated by crawling the web. <em>ZDNet </em>talked to Mike Tung, Diffbot's CEO and Founder, to find out how Diffbot does this.</p>\n<p>First off, you have to crawl the web. This is where <a href=\"https://www.gigablast.com/about.html\">Gigablast</a> and Matt Wells come in. Gigablast is a search engine created by Matt Wells, Diffbot's VP of Search, in 2000. Tung says this is what Diffbot uses to crawl, and store, every single document on the web. Hard as this may be, however, it's not even half the job.</p>\n<p>The really hard part is getting the information out of documents, and this is where the magic is. Tung explains this is done using computer vision, machine learning (ML), and natural language processing (NLP).</p>\n<p>Computer vision helps <a href=\"https://www.diffbot.com/\">Diffbot</a> understand the structure of documents. It mimics the way humans break down documents, figuring out what are the structural elements of each document -- things such as headers, blocks, etc. In a perfect world, this should be possible by inspecting the HTML structure of web documents. But not everything on the web is HTML, and HTML documents are not perfect either.</p>\n<p><strong>Also: <a href=\"https://www.zdnet.com/article/memsql-6-5-newsql-with-autonomous-workload-optimization-improved-data-ingestion-and-query-execution/\">MemSQL 6.5: NewSQL with autonomous workload optimization, improved data ingestion and query execution speed</a></strong></p>\n<p>After structure comes content. Content is parsed using a combination of NLP and ML, the result of which is structured knowledge which is added to <a href=\"https://www.diffbot.com/knowledge-graph\">Diffbot's knowledge graph</a> (DKG). Tung showcased an example based on Marissa Mayer, ex-CEO of Yahoo.</p>\n<p>Taking a brief text about Mayer as input, Diffbot's system processed it and was able to extract all kinds of facts described in the text: Mayer's gender, employment history, education, etc. By doing this, Diffbot adds an entry for Mayer in its knowledge graph, and populates it with properties such as gender, age, and the like.</p>\n<p>&quot;Contrary to popular perception, <a href=\"https://searchengineland.com/google-builds-next-gen-knowledge-graph-future-201640\">Google's knowledge graph is not derived primarily from automation</a>,&quot; says Tung. &quot;Unlike Google, the goal of our processing is not to rank pages for humans to read (and inject some advertising along the way), but rather to avoid human reading altogether.</p>\n<p>DKG is the first web-scale knowledge graph that is entirely synthesized by an <a href=\"https://www.zdnet.com/article/five-tech-jobs-that-ai-and-automation-will-make-radically-more-efficient/\">automated AI system</a>, without a human-in-the-loop. That is why the main constraint to growth is the number of machines that we dedicate to it acquiring knowledge,&quot; he adds, concluding that DKG currently contains something in the area of a trillion facts.</p>\n<h2>From a web of documents to a web of data</h2>\n<p>This is not entirely new. The first one who put forward the vision of going from a web of documents to a web of data was none other than the web's inventor, <a href=\"https://www-sop.inria.fr/acacia/fabien/lecture/licence_travaux_etude2002/TheSemanticWeb/\">Tim Berners Lee, who published his Semantic Web manifesto in 2001</a>.</p>\n<p>As Tung notes, however, &quot;a long line of history (ranging from RDF/microformats/RSS/semantic markup) has shown that requiring human annotation is never going to scale in terms of economic incentive and accuracy to all of knowledge.&quot;</p>\n<p>Even though annotation does not necessarily have to be human (it can come from automation as well), Tung does have a point: Most content on the web is very poorly, if at all, annotated. Tung thinks that building this global knowledge graph using the current state of AI is the right approach -- and it seems to be working.</p>\n<p><strong>Also: <a href=\"https://www.zdnet.com/article/moving-fast-without-breaking-data-governance-for-managing-risk-in-machine-learning-and-beyond/\">Moving fast without breaking data: Governance for managing risk in machine learning and beyond</a></strong></p>\n<p>The applications are wide and far-reaching. Tung notes that &quot;enterprise functions such as sales, recruiting, supply chain, accounting, business intelligence and market intelligence all work off of databases that can be kept updated and accurate by integrating directly with the knowledge graph.&quot;</p>\n<p>Tung demonstrated such a scenario, using DKG to query for people who work for Uber. Initially the query returned nearly 40,000 results, which Tung was able to filter using standard filtering as one would expect from a <a href=\"https://www.zdnet.com/article/the-new-era-of-the-multi-model-database/\">database</a>: Get only current employees, filter by region, etc.</p>\n<p>And that reference to integrating with databases has far-reaching implications too. The above scenario was based only on information found on the web. But enterprises don't just work with what they find on the web -- they also have their own internal systems and databases, and Tung says DKG can support those as well, offering one access point to rule them all.</p>\n<p><strong>Also: <a href=\"https://www.zdnet.com/article/graphql-for-databases-a-layer-for-universal-database-access/\">GraphQL for databases: A layer for universal database access?</a></strong></p>\n<p>DKG may well count as Diffbot's greatest achievement to date, but it did not come out of nowhere. Tung has strong credentials to show for, having designed web-scale information extraction architectures and worked for <a href=\"https://www.zdnet.com/topic/microsoft/\">Microsoft</a>, eBay, and Yahoo. Diffbot has been around since 2008, it has names such as eBay Microsoft Bing, and Salesforce among its clients, and Tencent and Bloomberg among its investors.</p>\n<p>Impressive as all of that may sound, however, there are a few gotchas.</p>\n<h2>Language, son</h2>\n<p>To begin with, not all of DKG is auto-magically created. That's not necessarily a bad thing, but it goes to show the limits of even what &quot;the current state of AI&quot; can do. DKG is seeded by Diffbot's knowledge engineers, who have decided that the entities it will handle are people, companies, locations, articles, products, discussions, and images.</p>\n<p>This means that everything Diffbot <a href=\"https://www.zdnet.com/article/robot-will-crawl-through-pipes-to-help-decommission-nuclear-facility/\">crawls</a> from the web will be classified as one of those things. Clearly, this decision was driven by what Diffbot's clients are mostly interested in, but that does not mean every page on the web is classified as one of the 20 types DKG currently knows. Tung says they plan to expand this to include categories such as events or medical information.</p>\n<p>In other words, Diffbot has consciously chosen to limit the scope of what it handles, to make a well-known problem manageable. To anyone familiar with <a href=\"http://connected-data.london/2018/06/11/building-enterprise-knowledge-graphs-in-the-real-world/\">knowledge graphs (also going by the name of ontologies for the connaisseurs</a>), what Diffbot does is defining an upper ontology, and populating it from the web. The concept and related challenges are well-known, but the way Diffbot handles this is state of the art.</p>\n<p><strong>Also: <a href=\"https://www.zdnet.com/article/aws-neptune-going-ga-the-good-the-bad-and-the-ugly-for-graph-database-users-and-vendors/\">AWS Neptune going GA: The good, the bad, and the ugly for graph database users and vendors</a></strong></p>\n<p>Which bring us to another key topic: Question answering. If you have the whole web at your fingertips, how are you going to query it? It depends. If you are a business person, ideally, you would like to use natural language. At present, DKG does not support this. It does, however, have its own Diffbot Query Language (DQL).</p>\n<p>DQL looks pretty simple, if you are familiar with query languages. But, then again, if you are familiar with query languages, why would you want to have to learn yet another one? There already is bunch of <a href=\"https://www.zdnet.com/article/back-to-the-future-does-graph-database-success-hang-on-query-language/\">graph query languages</a> out there, such as SPARQL, Gremlin, and OpenCypher, and with the <a href=\"https://www.zdnet.com/article/the-rise-and-rise-of-graph-databases/\">rise of graph databases</a>, we expect them to become more and more widespread.</p>\n<p>This touches upon another issue: Even though Diffbot's approach shares many similarities with semantic web concepts and standards (Tung even specifically mentioned <a href=\"https://www.zdnet.com/article/nba-analytics-and-rdf-graphs-game-data-and-metadata-evolution-and-occams-razor/\">RDF-like subject-predicate-object triples</a> in his breakdown of text processing), its approach is proprietary.</p>\n<p>Regardless of whether you know or like those standards, would it not have made Diffbot's life easier to use them? For example, by building DKG on top of an off-the-shelf graph database. Tung acknowledges it would, but he says they tested over a dozen <a href=\"http://yearofthegraph.xyz\">graph databases</a>, and they all broke down at around 10-100M entities, so they had to build something proprietary.</p>\n<p>As for the language issue, Tung says their approach is to meet users where they are, eliminating the need for directly using a query language (or an API, which DKG also supports) as much as possible. The way to do this, Tung says, is by integrating DKG with popular systems such as Salesforce, SAP, or Tableau, so users can transparently get data from DKG in their applications.</p>\n<p>That may be good for users, but it also places quite a burden of Diffbot to develop and maintain all those integrations. Tung says they intend to develop bridges for popular query languages, however, so integrations will not have to be hand-crafted.</p>\n<p><strong>Also: <a href=\"https://www.zdnet.com/article/planet-analytics-1-0-from-the-lab-to-production/\">Planet analytics 1.0: From the UN lab to the globe</a></strong></p>\n<p>Last but not least, does being able to query the web also mean you should automatically trust the results? Not necessarily. This is why Google and its ilk have developed sophisticated algorithms to rank results, trying to determine the most relevant ones. DKG only partially does this.</p>\n<p>You can filter Uber employees by age, for example, but what is the definitive source for that? If source X says a person was born in 1974, and source Y says they were born in 1947, which one should you trust? How do you know they are talking about the same person to begin with?</p>\n<p>These are well-known, hard-to-tackle issues, and Diffbot has to tackle them like anyone else who has come before them. Even as it is, however, DKG is an impressive achievement with many potential applications.</p>\n<h3>Previous and related coverage:</h3>\n<p><a href=\"https://www.zdnet.com/article/ai-chips-for-big-data-and-machine-learning-gpus-fpgas-and-hard-choices-in-the-cloud-and-on-premise/\"><strong>AI chips for big data and machine learning: GPUs, FPGAs, and hard choices in the cloud and on-premise</strong></a></p>\n<p>How can GPUs and FPGAs help with data-intensive tasks such as operations, analytics, and machine learning, and what are the options?</p>\n<p><a href=\"https://www.zdnet.com/article/data-driven-disaster-relief-measuring-the-impact-of-emergency-response/\"><strong>Data-driven disaster relief: Measuring the impact of emergency response</strong></a></p>\n<p>With natural disasters picking up in frequency and intensity, the role of NGOs in disaster relief is picking up as well. A key requirement for all NGOs is transparency, and applying data-driven techniques may help.</p>\n<p><a href=\"https://www.zdnet.com/article/wolfram-research-goes-for-software-2-0-releases-neural-net-repository/\"><strong>Wolfram Research goes for Software 2.0, releases neural net repository</strong></a></p>\n<p>Wolfram, having been into AI before it was cool, now gets a piece of the deep learning hype, in its sui generis way. Where does it stand compared to the competition, and how easy is it to use and integrate Wolfram with the rest of the world?</p>"
 }
 ```
 ### icon
@@ -184,7 +240,16 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"icon": "https://zdnet2.cbsistatic.com/fly/bundles/zdnetcss/images/logos/logo-192x192.png"
+	"icon": "https://www.zdnet.com/a/fly/bundles/zdnetcore/images/logos/zdnet-logo-yellow.png"
+}
+```
+### id
+  Each entity in the Diffbot KnowledgeGraph (DKG) is identified by a unique identifier, an alphanumeric string like CWSwJ_SWQPfqO3HQsxY4lGg that uniquely identifies that entity. The id is directly derived from the most authoritative origin from the origins array.
+* **Type:** String
+* **Example:**
+```
+{
+	"id": "ART96037639621"
 }
 ```
 ### images
@@ -196,21 +261,11 @@ Note that certain longer field examples may be truncated for readability.
 	"images": [
 		{
 			"summary": "",
-			"image": "https://zdnet2.cbsistatic.com/hub/i/r/2018/08/30/ad927664-7ba0-4352-a3d7-6c3efdd8a18d/resize/470xauto/466e3fcf32bac06b562faa1ae8637f74/opera-snapshot2018-08-30101415www-diffbot-com.png",
-			"naturalHeight": 186,
-			"name": "Diffbot ingests and parses the entire web into a knowledge graph - a database you can query. Image: Diffbot",
-			"title": "Diffbot ingests and parses the entire web into a knowledge graph - a database you can query. Image: Diffbot",
-			"url": "https://zdnet2.cbsistatic.com/hub/i/r/2018/08/30/ad927664-7ba0-4352-a3d7-6c3efdd8a18d/resize/470xauto/466e3fcf32bac06b562faa1ae8637f74/opera-snapshot2018-08-30101415www-diffbot-com.png",
-			"naturalWidth": 470
-		},
-		{
-			"summary": "",
-			"image": "https://zdnet3.cbsistatic.com/hub/i/r/2018/08/30/79b11205-86a0-4b60-ad1a-658a49e3bcc1/resize/470xauto/287cba267d3c5cbb262778944f9d1eb3/diffbot-kg-record-linking.jpg",
-			"naturalHeight": 347,
-			"name": "Diffbot natural language processing in action. Note how facts extracted from text are represented as subject -- predicate -- object triples. (Image: Diffbot)",
-			"title": "Diffbot natural language processing in action. Note how facts extracted from text are represented as subject -- predicate -- object triples. (Image: Diffbot)",
-			"url": "https://zdnet3.cbsistatic.com/hub/i/r/2018/08/30/79b11205-86a0-4b60-ad1a-658a49e3bcc1/resize/470xauto/287cba267d3c5cbb262778944f9d1eb3/diffbot-kg-record-linking.jpg",
-			"naturalWidth": 470
+			"image": "https://www.zdnet.com/a/img/resize/28753f7b6fe517051d38dfa7436268bc9ad26753/2017/11/03/39e92e2e-027b-46b5-b15a-11f3844919a9/59ef6a2260b25a01359a7201-1280x7201nov032017164306poster.jpg?auto=webp&fit=crop&frame=1&height=814.5&width=1449",
+			"naturalHeight": 0,
+			"name": "",
+			"url": "https://www.zdnet.com/a/img/resize/28753f7b6fe517051d38dfa7436268bc9ad26753/2017/11/03/39e92e2e-027b-46b5-b15a-11f3844919a9/59ef6a2260b25a01359a7201-1280x7201nov032017164306poster.jpg?auto=webp&fit=crop&frame=1&height=814.5&width=1449",
+			"naturalWidth": 0
 		}
 	]
 }
@@ -251,6 +306,15 @@ Note that certain longer field examples may be truncated for readability.
 	"numPages": 0
 }
 ```
+### pageUrl
+  URL of submitted page &#x2F; page from which the entity is extracted
+* **Type:** String
+* **Example:**
+```
+{
+	"pageUrl": "https://www.zdnet.com/article/the-web-as-a-database-the-biggest-knowledge-graph-ever/"
+}
+```
 ### publisherCountry
   
 * **Type:** String
@@ -277,20 +341,29 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"quotes": [
 		{
-			"speakerUri": "",
-			"quote": "",
-			"speaker": ""
+			"speakerUri": "https://diffbot.com/entity/ESGMaGV9uP0SuTmfPTtNEoA",
+			"quote": "Unlike Google, the goal of our processing is not to rank pages for humans to read (and inject some advertising along the way), but rather to avoid human reading altogether.\nDKG is the first web-scale knowledge graph that is entirely synthesized by an automated AI system, without a human-in-the-loop. That is why the main constraint to growth is the number of machines that we dedicate to it acquiring knowledge.",
+			"speaker": "Mike Tung"
 		}
 	]
 }
 ```
+### resolvedPageUrl
+  Returned if the pageUrl redirects to another URL
+* **Type:** String
+* **Example:**
+```
+{
+	"resolvedPageUrl": ""
+}
+```
 ### sentiment
   Sentiment of the article. Positive sentiments have positive values and negative sentiments have a negative value.
 * **Type:** Float
 * **Example:**
 ```
 {
-	"sentiment": 0.0049
+	"sentiment": 0.344
 }
 ```
 ### siteName
@@ -299,7 +372,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"siteName": "ZDNet"
+	"siteName": "ZDNET"
 }
 ```
 ### tags
@@ -310,36 +383,24 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"tags": [
 		{
-			"score": 0.94,
-			"sentiment": -0.15,
+			"score": 0.86172557,
+			"sentiment": 0,
 			"types": [
-				"http://dbpedia.org/ontology/Agent",
-				"http://dbpedia.org/ontology/Organisation",
-				"http://dbpedia.org/ontology/Media",
-				"http://dbpedia.org/ontology/Identifier",
-				"http://dbpedia.org/ontology/Work",
-				"http://dbpedia.org/ontology/Activity",
-				"http://dbpedia.org/ontology/Software"
+				"http://dbpedia.org/ontology/Person"
 			],
-			"count": 12,
-			"label": "Knowledge Graph",
-			"uri": "http://dbpedia.org/page/Knowledge_Graph"
+			"count": 8,
+			"label": "Mike Tung",
+			"uri": "http://diffbot.com/entity/ESGMaGV9uP0SuTmfPTtNEoA"
 		},
 		{
-			"score": 0.62,
-			"count": 2,
-			"label": "Artificial intelligence",
-			"uri": "http://dbpedia.org/page/Artificial_intelligence"
-		},
-		{
-			"score": 0.58,
+			"score": 0.6859183,
+			"sentiment": 0,
 			"types": [
-				"http://dbpedia.org/ontology/Agent",
-				"http://dbpedia.org/ontology/Person"
+				"http://dbpedia.org/ontology/Skill"
 			],
 			"count": 1,
-			"label": "Marissa Mayer",
-			"uri": "http://dbpedia.org/page/Marissa_Mayer"
+			"label": "knowledge graph",
+			"uri": "http://diffbot.com/entity/ElFkUuZDoOCi4bbCcCTf1zw"
 		}
 	]
 }
@@ -350,7 +411,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"text": "The web is among humankind's greatest achievements and resources. Ever-expanding and nearly all-encompassing, we've all come to depend on it. There's just one problem: It takes work to get information out of it.\nThat's because the information is in documents, and documents on the web are all over the place, and someone needs to locate them, and read them, to extract that information. Search engines have come a long way, and they greatly assist in the locating part, but not so much in the extracting part. At least, not until today.\nAlso: Zen and the art of data structures: From self-tuning to self-designing data systems\nGoogle and its ilk may sometimes give the impression they can understand and answer questions. Part of the reason is the addition of human knowledge in the mix. Google famously went from using purely text-based and statistical methods to adding a form of curation when it bought MetaWeb. MetaWeb developed Freebase, which was a crowd-sourced knowledge graph, similar in approach to Wikipedia, which was integrated in Google's search engine.\nEat your heart out, Google\nThat enables Google to do some of its magic. If you Google \"Google,\" for example, you don't just get a bunch of links. You also get an info-box that lists facts such as Google's CEO, founders, and address. That's because there is an entry in Google's knowledge graph that lists Google as a company, and these are some of the properties companies have, so Google fetches and displays that information from Wikipedia.\nBut if you try Googling \"how many employees does Google have,\" or \"what is Google's address\", what you will get is a bunch of links. You are on your own -- you have to read the documents and figure out the answer. If that information was in a database, you would type something like \"SELECT Address FROM Organizations WHERE Name=Google\" and you'd have your answer in seconds. That is the difference between structured and unstructured information.\nAlso: MemSQL 6.5: NewSQL with autonomous workload optimization, improved data ingestion and query execution speed\nThat is also what Diffbot is unveiling today: The ability to query the web as a database. This impressive feat is also based on a knowledge graph. The difference is that, in Diffbot's case, the knowledge graph is only partially curated by humans, and is automatically populated by crawling the web. ZDNet talked to Mike Tung, Diffbot's CEO and Founder, to find out how Diffbot does this.\nFirst off, you have to crawl the web. This is where Gigablast and Matt Wells come in. Gigablast is a search engine created by Matt Wells, Diffbot's VP of Search, in 2000. Tung says this is what Diffbot uses to crawl, and store, every single document on the web. Hard as this may be, however, it's not even half the job.\nThe really hard part is getting the information out of documents, and this is where the magic is. Tung explains this is done using computer vision, machine learning (ML), and natural language processing (NLP).\nComputer vision helps Diffbot understand the structure of documents. It mimics the way humans break down documents, figuring out what are the structural elements of each document -- things such as headers, blocks, etc. In a perfect world, this should be possible by inspecting the HTML structure of web documents. But not everything on the web is HTML, and HTML documents are not perfect either.\nAlso: MemSQL 6.5: NewSQL with autonomous workload optimization, improved data ingestion and query execution speed\nAfter structure comes content. Content is parsed using a combination of NLP and ML, the result of which is structured knowledge which is added to Diffbot's knowledge graph (DKG). Tung showcased an example based on Marissa Mayer, ex-CEO of Yahoo.\nTaking a brief text about Mayer as input, Diffbot's system processed it and was able to extract all kinds of facts described in the text: Mayer's gender, employment history, education, etc. By doing this, Diffbot adds an entry for Mayer in its knowledge graph, and populates it with properties such as gender, age, and the like.\n\"Contrary to popular perception, Google's knowledge graph is not derived primarily from automation,\" says Tung. \"Unlike Google, the goal of our processing is not to rank pages for humans to read (and inject some advertising along the way), but rather to avoid human reading altogether.\nDKG is the first web-scale knowledge graph that is entirely synthesized by an automated AI system, without a human-in-the-loop. That is why the main constraint to growth is the number of machines that we dedicate to it acquiring knowledge,\" he adds, concluding that DKG currently contains something in the area of one billion facts.\nFrom a web of documents to a web of data\nThis is not entirely new. The first one who put forward the vision of going from a web of documents to a web of data was none other than the web's inventor, Tim Berners Lee, who published his Semantic Web manifesto in 2001.\nAs Tung notes, however, \"a long line of history (ranging from RDF/microformats/RSS/semantic markup) has shown that requiring human annotation is never going to scale in terms of economic incentive and accuracy to all of knowledge.\"\nEven though annotation does not necessarily have to be human (it can come from automation as well), Tung does have a point: Most content on the web is very poorly, if at all, annotated. Tung thinks that building this global knowledge graph using the current state of AI is the right approach -- and it seems to be working.\nAlso: Moving fast without breaking data: Governance for managing risk in machine learning and beyond\nThe applications are wide and far-reaching. Tung notes that \"enterprise functions such as sales, recruiting, supply chain, accounting, business intelligence and market intelligence all work off of databases that can be kept updated and accurate by integrating directly with the knowledge graph.\"\nTung demonstrated such a scenario, using DKG to query for people who work for Uber. Initially the query returned nearly 40,000 results, which Tung was able to filter using standard filtering as one would expect from a database: Get only current employees, filter by region, etc.\nAnd that reference to integrating with databases has far-reaching implications too. The above scenario was based only on information found on the web. But enterprises don't just work with what they find on the web -- they also have their own internal systems and databases, and Tung says DKG can support those as well, offering one access point to rule them all.\nAlso: GraphQL for databases: A layer for universal database access?\nDKG may well count as Diffbot's greatest achievement to date, but it did not come out of nowhere. Tung has strong credentials to show for, having designed web-scale information extraction architectures and worked for Microsoft, eBay, and Yahoo. Diffbot has been around since 2008, it has names such as eBay Microsoft Bing, and Salesforce among its clients, and Tencent and Bloomberg among its investors.\nImpressive as all of that may sound, however, there are a few gotchas.\nLanguage, son\nTo begin with, not all of DKG is auto-magically created. That's not necessarily a bad thing, but it goes to show the limits of even what \"the current state of AI\" can do. DKG is seeded by Diffbot's knowledge engineers, who have decided that the entities it will handle are people, companies, locations, articles, products, discussions, and images.\nThis means that everything Diffbot crawls from the web will be classified as one of those things. Clearly, this decision was driven by what Diffbot's clients are mostly interested in, but that does not mean every page on the web is classified as one of the 20 types DKG currently knows. Tung says they plan to expand this to include categories such as events or medical information.\nIn other words, Diffbot has consciously chosen to limit the scope of what it handles, to make a well-known problem manageable. To anyone familiar with knowledge graphs (also going by the name of ontologies for the connaisseurs), what Diffbot does is defining an upper ontology, and populating it from the web. The concept and related challenges are well-known, but the way Diffbot handles this is state of the art.\nAlso: AWS Neptune going GA: The good, the bad, and the ugly for graph database users and vendors\nWhich bring us to another key topic: Question answering. If you have the whole web at your fingertips, how are you going to query it? It depends. If you are a business person, ideally, you would like to use natural language. At present, DKG does not support this. It does, however, have its own Diffbot Query Language (DQL).\nDQL looks pretty simple, if you are familiar with query languages. But, then again, if you are familiar with query languages, why would you want to have to learn yet another one? There already is bunch of graph query languages out there, such as SPARQL, Gremlin, and OpenCypher, and with the rise of graph databases, we expect them to become more and more widespread.\nThis touches upon another issue: Even though Diffbot's approach shares many similarities with semantic web concepts and standards (Tung even specifically mentioned RDF-like subject-predicate-object triples in his breakdown of text processing), its approach is proprietary.\nRegardless of whether you know or like those standards, would it not have made Diffbot's life easier to use them? For example, by building DKG on top of an off-the-shelf graph database. Tung acknowledges it would, but he says they tested over a dozen graph databases, and they all broke down at around 10-100M entities, so they had to build something proprietary.\nAs for the language issue, Tung says their approach is to meet users where they are, eliminating the need for directly using a query language (or an API, which DKG also supports) as much as possible. The way to do this, Tung says, is by integrating DKG with popular systems such as Salesforce, SAP, or Tableau, so users can transparently get data from DKG in their applications.\nThat may be good for users, but it also places quite a burden of Diffbot to develop and maintain all those integrations. Tung says they intend to develop bridges for popular query languages, however, so integrations will not have to be hand-crafted.\nAlso: Planet analytics 1.0: From the UN lab to the globe\nLast but not least, does being able to query the web also mean you should automatically trust the results? Not necessarily. This is why Google and its ilk have developed sophisticated algorithms to rank results, trying to determine the most relevant ones. DKG only partially does this.\nYou can filter Uber employees by age, for example, but what is the definitive source for that? If source X says a person was born in 1974, and source Y says they were born in 1947, which one should you trust? How do you know they are talking about the same person to begin with?\nThese are well-known, hard-to-tackle issues, and Diffbot has to tackle them like anyone else who has come before them. Even as it is, however, DKG is an impressive achievement with many potential applications.\nAI chips for big data and machine learning: GPUs, FPGAs, and hard choices in the cloud and on-premise\nHow can GPUs and FPGAs help with data-intensive tasks such as operations, analytics, and machine learning, and what are the options?\nWith natural disasters picking up in frequency and intensity, the role of NGOs in disaster relief is picking up as well. A key requirement for all NGOs is transparency, and applying data-driven techniques may help.\nWolfram, having been into AI before it was cool, now gets a piece of the deep learning hype, in its sui generis way. Where does it stand compared to the competition, and how easy is it to use and integrate Wolfram with the rest of the world?"
+	"text": "The web is among humankind's greatest achievements and resources. Ever-expanding and nearly all-encompassing, we've all come to depend on it. There's just one problem: It takes work to get information out of it.\nFeatured\nI asked ChatGPT, Bing, and Bard what worries them. Google's AI went Terminator on me\n8 habits of highly-secure remote workers\nThis tiny satellite communicator is packed full of features and peace of mind\nThe best Android smartwatches (and which ones can function without a phone)\nThat's because the information is in documents, and documents on the web are all over the place, and someone needs to locate them, and read them, to extract that information. Search engines have come a long way, and they greatly assist in the locating part, but not so much in the extracting part. At least, not until today.\nAlso: Zen and the art of data structures: From self-tuning to self-designing data systems\nGoogle and its ilk may sometimes give the impression they can understand and answer questions. Part of the reason is the addition of human knowledge in the mix. Google famously went from using purely text-based and statistical methods to adding a form of curation when it bought MetaWeb. MetaWeb developed Freebase, which was a crowd-sourced knowledge graph, similar in approach to Wikipedia, which was integrated in Google's search engine.\nEat your heart out, Google\nThat enables Google to do some of its magic. If you Google \"Google,\" for example, you don't just get a bunch of links. You also get an info-box that lists facts such as Google's CEO, founders, and address. That's because there is an entry in Google's knowledge graph that lists Google as a company, and these are some of the properties companies have, so Google fetches and displays that information from Wikipedia.\nBut if you try Googling \"how many employees does Google have,\" or \"what is Google's address\", what you will get is a bunch of links. You are on your own -- you have to read the documents and figure out the answer. If that information was in a database, you would type something like \"SELECT Address FROM Organizations WHERE Name=Google\" and you'd have your answer in seconds. That is the difference between structured and unstructured information.\nAlso: MemSQL 6.5: NewSQL with autonomous workload optimization, improved data ingestion and query execution speed\nThat is also what Diffbot is unveiling today: The ability to query the web as a database. This impressive feat is also based on a knowledge graph. The difference is that, in Diffbot's case, the knowledge graph is only partially curated by humans, and is automatically populated by crawling the web. ZDNet talked to Mike Tung, Diffbot's CEO and Founder, to find out how Diffbot does this.\nFirst off, you have to crawl the web. This is where Gigablast and Matt Wells come in. Gigablast is a search engine created by Matt Wells, Diffbot's VP of Search, in 2000. Tung says this is what Diffbot uses to crawl, and store, every single document on the web. Hard as this may be, however, it's not even half the job.\nThe really hard part is getting the information out of documents, and this is where the magic is. Tung explains this is done using computer vision, machine learning (ML), and natural language processing (NLP).\nComputer vision helps Diffbot understand the structure of documents. It mimics the way humans break down documents, figuring out what are the structural elements of each document -- things such as headers, blocks, etc. In a perfect world, this should be possible by inspecting the HTML structure of web documents. But not everything on the web is HTML, and HTML documents are not perfect either.\nAlso: MemSQL 6.5: NewSQL with autonomous workload optimization, improved data ingestion and query execution speed\nAfter structure comes content. Content is parsed using a combination of NLP and ML, the result of which is structured knowledge which is added to Diffbot's knowledge graph (DKG). Tung showcased an example based on Marissa Mayer, ex-CEO of Yahoo.\nTaking a brief text about Mayer as input, Diffbot's system processed it and was able to extract all kinds of facts described in the text: Mayer's gender, employment history, education, etc. By doing this, Diffbot adds an entry for Mayer in its knowledge graph, and populates it with properties such as gender, age, and the like.\n\"Contrary to popular perception, Google's knowledge graph is not derived primarily from automation,\" says Tung. \"Unlike Google, the goal of our processing is not to rank pages for humans to read (and inject some advertising along the way), but rather to avoid human reading altogether.\nDKG is the first web-scale knowledge graph that is entirely synthesized by an automated AI system, without a human-in-the-loop. That is why the main constraint to growth is the number of machines that we dedicate to it acquiring knowledge,\" he adds, concluding that DKG currently contains something in the area of a trillion facts.\nFrom a web of documents to a web of data\nThis is not entirely new. The first one who put forward the vision of going from a web of documents to a web of data was none other than the web's inventor, Tim Berners Lee, who published his Semantic Web manifesto in 2001.\nAs Tung notes, however, \"a long line of history (ranging from RDF/microformats/RSS/semantic markup) has shown that requiring human annotation is never going to scale in terms of economic incentive and accuracy to all of knowledge.\"\nEven though annotation does not necessarily have to be human (it can come from automation as well), Tung does have a point: Most content on the web is very poorly, if at all, annotated. Tung thinks that building this global knowledge graph using the current state of AI is the right approach -- and it seems to be working.\nAlso: Moving fast without breaking data: Governance for managing risk in machine learning and beyond\nThe applications are wide and far-reaching. Tung notes that \"enterprise functions such as sales, recruiting, supply chain, accounting, business intelligence and market intelligence all work off of databases that can be kept updated and accurate by integrating directly with the knowledge graph.\"\nTung demonstrated such a scenario, using DKG to query for people who work for Uber. Initially the query returned nearly 40,000 results, which Tung was able to filter using standard filtering as one would expect from a database: Get only current employees, filter by region, etc.\nAnd that reference to integrating with databases has far-reaching implications too. The above scenario was based only on information found on the web. But enterprises don't just work with what they find on the web -- they also have their own internal systems and databases, and Tung says DKG can support those as well, offering one access point to rule them all.\nAlso: GraphQL for databases: A layer for universal database access?\nDKG may well count as Diffbot's greatest achievement to date, but it did not come out of nowhere. Tung has strong credentials to show for, having designed web-scale information extraction architectures and worked for Microsoft, eBay, and Yahoo. Diffbot has been around since 2008, it has names such as eBay Microsoft Bing, and Salesforce among its clients, and Tencent and Bloomberg among its investors.\nImpressive as all of that may sound, however, there are a few gotchas.\nLanguage, son\nTo begin with, not all of DKG is auto-magically created. That's not necessarily a bad thing, but it goes to show the limits of even what \"the current state of AI\" can do. DKG is seeded by Diffbot's knowledge engineers, who have decided that the entities it will handle are people, companies, locations, articles, products, discussions, and images.\nThis means that everything Diffbot crawls from the web will be classified as one of those things. Clearly, this decision was driven by what Diffbot's clients are mostly interested in, but that does not mean every page on the web is classified as one of the 20 types DKG currently knows. Tung says they plan to expand this to include categories such as events or medical information.\nIn other words, Diffbot has consciously chosen to limit the scope of what it handles, to make a well-known problem manageable. To anyone familiar with knowledge graphs (also going by the name of ontologies for the connaisseurs), what Diffbot does is defining an upper ontology, and populating it from the web. The concept and related challenges are well-known, but the way Diffbot handles this is state of the art.\nAlso: AWS Neptune going GA: The good, the bad, and the ugly for graph database users and vendors\nWhich bring us to another key topic: Question answering. If you have the whole web at your fingertips, how are you going to query it? It depends. If you are a business person, ideally, you would like to use natural language. At present, DKG does not support this. It does, however, have its own Diffbot Query Language (DQL).\nDQL looks pretty simple, if you are familiar with query languages. But, then again, if you are familiar with query languages, why would you want to have to learn yet another one? There already is bunch of graph query languages out there, such as SPARQL, Gremlin, and OpenCypher, and with the rise of graph databases, we expect them to become more and more widespread.\nThis touches upon another issue: Even though Diffbot's approach shares many similarities with semantic web concepts and standards (Tung even specifically mentioned RDF-like subject-predicate-object triples in his breakdown of text processing), its approach is proprietary.\nRegardless of whether you know or like those standards, would it not have made Diffbot's life easier to use them? For example, by building DKG on top of an off-the-shelf graph database. Tung acknowledges it would, but he says they tested over a dozen graph databases, and they all broke down at around 10-100M entities, so they had to build something proprietary.\nAs for the language issue, Tung says their approach is to meet users where they are, eliminating the need for directly using a query language (or an API, which DKG also supports) as much as possible. The way to do this, Tung says, is by integrating DKG with popular systems such as Salesforce, SAP, or Tableau, so users can transparently get data from DKG in their applications.\nThat may be good for users, but it also places quite a burden of Diffbot to develop and maintain all those integrations. Tung says they intend to develop bridges for popular query languages, however, so integrations will not have to be hand-crafted.\nAlso: Planet analytics 1.0: From the UN lab to the globe\nLast but not least, does being able to query the web also mean you should automatically trust the results? Not necessarily. This is why Google and its ilk have developed sophisticated algorithms to rank results, trying to determine the most relevant ones. DKG only partially does this.\nYou can filter Uber employees by age, for example, but what is the definitive source for that? If source X says a person was born in 1974, and source Y says they were born in 1947, which one should you trust? How do you know they are talking about the same person to begin with?\nThese are well-known, hard-to-tackle issues, and Diffbot has to tackle them like anyone else who has come before them. Even as it is, however, DKG is an impressive achievement with many potential applications.\nPrevious and related coverage:\nAI chips for big data and machine learning: GPUs, FPGAs, and hard choices in the cloud and on-premise\nHow can GPUs and FPGAs help with data-intensive tasks such as operations, analytics, and machine learning, and what are the options?\nData-driven disaster relief: Measuring the impact of emergency response\nWith natural disasters picking up in frequency and intensity, the role of NGOs in disaster relief is picking up as well. A key requirement for all NGOs is transparency, and applying data-driven techniques may help.\nWolfram Research goes for Software 2.0, releases neural net repository\nWolfram, having been into AI before it was cool, now gets a piece of the deep learning hype, in its sui generis way. Where does it stand compared to the competition, and how easy is it to use and integrate Wolfram with the rest of the world?"
 }
 ```
 ### title
@@ -362,6 +423,26 @@ Note that certain longer field examples may be truncated for readability.
 	"title": "The web as a database: The biggest knowledge graph ever"
 }
 ```
+### type
+  The top-level type of a Diffbot entity. Examples of type include Person, Organization, Article, Product.
+* **Type:** Type
+* **Example:**
+```
+{
+	"type": "Article"
+}
+```
+### types
+  There are tags.types which can only refer to dbpedia rdf types, while there are also the general DiffbotEntity types which is just an array of all the types an object belongs to. For instance a LocalBusiness would have &#x60;types:[&quot;Organization&quot;,&quot;LocalBusiness&quot;]&#x60; Finally, there are types that indicate a belonging to a subgroup such as business vs personal email address.
+* **Type:** String
+* **Example:**
+```
+{
+	"types": [
+		"Article"
+	]
+}
+```
 ### videos
   
 * **Type:** GlobalIndexVideo
diff --git a/docs/kg-ont-creativework.md b/docs/kg-ont-creativework.md
index 1eedc589..0d04b00e 100644
--- a/docs/kg-ont-creativework.md
+++ b/docs/kg-ont-creativework.md
@@ -1,103 +1,30 @@
 ---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
 id: kg-ont-creativework
 title: CreativeWork
+generatedBy: generateOntology.js
 ---
 
 The Creative Work entity type encompasses movies, tv shows, musicals, scripts, and other creative works known to the Knowledge Graph. 
 
 Note that fields are not guaranteed to exist in every entity record.
 
->New to the Diffbot Knowledge Graph? [Start here](dql-quickstart).
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
 
 ## CreativeWork Fields
-* [RSS feed](#rss feed) 
-* [appleGuid](#appleguid) 
-* [artistCredit](#artistcredit) 
-* [aspectRatio](#aspectratio) 
 * [authors](#authors) 
-* [boxOfficeGrossUsa](#boxofficegrossusa) 
-* [boxOfficeOpeningWeekendUsa](#boxofficeopeningweekendusa) 
-* [boxOfficeWorldGross](#boxofficeworldgross) 
-* [budget](#budget) 
-* [castmembers](#castmembers) 
-* [color](#color) 
-* [complete](#complete) 
-* [countryOfOrigin](#countryoforigin) 
-* [creativeWorkType](#creativeworktype) 
-* [creators](#creators) 
-* [creditedArtists](#creditedartists) 
-* [directors](#directors) 
-* [episodeNum](#episodenum) 
-* [explicit](#explicit) 
-* [genres](#genres) 
-* [guests](#guests) 
-* [imdbPopularity](#imdbpopularity) 
-* [imdbRating](#imdbrating) 
 * [imdbUri](#imdburi) 
-* [languages](#languages) 
-* [latestSeason](#latestseason) 
-* [latestSeasonYear](#latestseasonyear) 
-* [metaScore](#metascore) 
-* [mpaaRating](#mpaarating) 
 * [musicbrainzUri](#musicbrainzuri) 
-* [numAwards](#numawards) 
-* [numEpisodes](#numepisodes) 
-* [numTracks](#numtracks) 
-* [officialSites](#officialsites) 
 * [parentTitle](#parenttitle) 
-* [plotKeywords](#plotkeywords) 
-* [plotSummary](#plotsummary) 
-* [podCategories](#podcategories) 
-* [podDescription](#poddescription) 
-* [posterImgLink](#posterimglink) 
-* [productionCompanies](#productioncompanies) 
-* [releaseDate](#releasedate) 
-* [runtime](#runtime) 
-* [seasonNum](#seasonnum) 
-* [taglines](#taglines) 
-* [trackPosition](#trackposition) 
-* [videoMainLink](#videomainlink) 
-* [writers](#writers) 
 
 ## CreativeWork Field Details
 Note that certain longer field examples may be truncated for readability.
 
-### RSS feed
-  
-* **Type:** URL
-* **Example:**
-```
-{
-	"RSS feed": ""
-}
-```
-### appleGuid
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"appleGuid": ""
-}
-```
-### artistCredit
-  Artist Credit String
-* **Type:** String
-* **Example:**
-```
-{
-	"artistCredit": ""
-}
-```
-### aspectRatio
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"aspectRatio": "1.78 : 1"
-}
-```
 ### authors
   
 * **Type:** LinkedEntity
@@ -118,345 +45,23 @@ Note that certain longer field examples may be truncated for readability.
 				}
 			],
 			"types": "",
-			"websiteUris": "",
-			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
-		}
-	]
-}
-```
-### boxOfficeGrossUsa
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"boxOfficeGrossUsa": ""
-}
-```
-### boxOfficeOpeningWeekendUsa
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"boxOfficeOpeningWeekendUsa": ""
-}
-```
-### boxOfficeWorldGross
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"boxOfficeWorldGross": ""
-}
-```
-### budget
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"budget": ""
-}
-```
-### castmembers
-  
-* **Type:** CastMember
-* **Example:**
-```
-{
-	"castmembers": [
-		{
-			"castmember": {
-				"recordId": "ErgKVmOjIOeiFEge88_z0Ow@0",
-				"name": "Joni Mitchell",
-				"websiteUris": [
-					"imdb.com/name/nm0593474"
-				],
-				"surfaceForm": "Joni Mitchell",
-				"type": "Person"
-			}
-		},
-		{
-			"castmember": {
-				"recordId": "ErgKVmOjIOeiFEge88_z0Ow@1",
-				"name": "Bill Flanagan",
-				"websiteUris": [
-					"imdb.com/name/nm1940634"
-				],
-				"surfaceForm": "Bill Flanagan",
-				"type": "Person"
-			}
-		},
-		{
-			"castmember": {
-				"recordId": "ErgKVmOjIOeiFEge88_z0Ow@2",
-				"name": "David Crosby",
-				"websiteUris": [
-					"imdb.com/name/nm0004849"
-				],
-				"surfaceForm": "David Crosby",
-				"type": "Person"
-			}
-		}
-	]
-}
-```
-### color
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"color": "Color | Black and White"
-}
-```
-### complete
-  
-* **Type:** Boolean
-* **Example:**
-```
-{
-	"complete": false
-}
-```
-### countryOfOrigin
-  This indicates where the work is created. Usually where the production companies or original publisher are from.
-* **Type:** String
-* **Example:**
-```
-{
-	"countryOfOrigin": [
-		"USA"
-	]
-}
-```
-### creativeWorkType
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"creativeWorkType": "tv episode"
-}
-```
-### creators
-  
-* **Type:** LinkedEntity
-* **Example:**
-```
-{
-	"creators": [
-		{
-			"summary": "",
-			"image": "",
-			"images": [
-				{
-					"classifications": "",
-					"fingerprint": "",
-					"title": "",
-					"isCached": false,
-					"url": ""
-				}
-			],
-			"types": "",
-			"websiteUris": "",
-			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
-		}
-	]
-}
-```
-### creditedArtists
-  List of credited artists
-* **Type:** LinkedEntity
-* **Example:**
-```
-{
-	"creditedArtists": [
-		{
-			"summary": "",
-			"image": "",
-			"images": [
-				{
-					"classifications": "",
-					"fingerprint": "",
-					"title": "",
-					"isCached": false,
-					"url": ""
-				}
-			],
-			"types": "",
-			"websiteUris": "",
-			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
-		}
-	]
-}
-```
-### directors
-  
-* **Type:** LinkedEntity
-* **Example:**
-```
-{
-	"directors": [
-		{
-			"recordId": "ErgKVmOjIOeiFEge88_z0Ow@18",
-			"name": "Susan Lacy",
-			"websiteUris": [
-				"imdb.com/name/nm0480402"
-			],
-			"surfaceForm": "Susan Lacy",
-			"position": "creativeWorkDirector",
-			"type": "Person"
-		}
-	]
-}
-```
-### episodeNum
-  
-* **Type:** Integer
-* **Example:**
-```
-{
-	"episodeNum": 5
-}
-```
-### explicit
-  
-* **Type:** Boolean
-* **Example:**
-```
-{
-	"explicit": false
-}
-```
-### genres
-  Genres of the work. It can be multiple genres.
-* **Type:** String
-* **Example:**
-```
-{
-	"genres": [
-		"Documentary",
-		"Biography"
-	]
-}
-```
-### guests
-  
-* **Type:** LinkedEntity
-* **Example:**
-```
-{
-	"guests": [
-		{
-			"summary": "",
-			"image": "",
-			"images": [
-				{
-					"classifications": "",
-					"fingerprint": "",
-					"title": "",
-					"isCached": false,
-					"url": ""
-				}
-			],
-			"types": "",
-			"websiteUris": "",
 			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
+			"name": ""
 		}
 	]
 }
 ```
-### imdbPopularity
-  
-* **Type:** Float
-* **Example:**
-```
-{
-	"imdbPopularity": ""
-}
-```
-### imdbRating
-  
-* **Type:** Float
-* **Example:**
-```
-{
-	"imdbRating": 7.9
-}
-```
 ### imdbUri
-  
+  Link to the IMDB profile of this entity
 * **Type:** URL
 * **Example:**
 ```
 {
-	"imdbUri": "imdb.com/title/tt0778181"
-}
-```
-### languages
-  This is the language in which the work is originally created.
-* **Type:** String
-* **Example:**
-```
-{
-	"languages": [
-		"English"
-	]
-}
-```
-### latestSeason
-  
-* **Type:** Integer
-* **Example:**
-```
-{
-	"latestSeason": 0
-}
-```
-### latestSeasonYear
-  
-* **Type:** Integer
-* **Example:**
-```
-{
-	"latestSeasonYear": 0
-}
-```
-### metaScore
-  
-* **Type:** Float
-* **Example:**
-```
-{
-	"metaScore": ""
-}
-```
-### mpaaRating
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"mpaaRating": ""
+	"imdbUri": "imdb.com/title/tt1052005"
 }
 ```
 ### musicbrainzUri
-  
+  Link to the Musicbrainz profile of this entity
 * **Type:** URL
 * **Example:**
 ```
@@ -464,42 +69,6 @@ Note that certain longer field examples may be truncated for readability.
 	"musicbrainzUri": ""
 }
 ```
-### numAwards
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"numAwards": ""
-}
-```
-### numEpisodes
-  
-* **Type:** Integer
-* **Example:**
-```
-{
-	"numEpisodes": 0
-}
-```
-### numTracks
-  
-* **Type:** Integer
-* **Example:**
-```
-{
-	"numTracks": 0
-}
-```
-### officialSites
-  
-* **Type:** URL
-* **Example:**
-```
-{
-	"officialSites": []
-}
-```
 ### parentTitle
   
 * **Type:** LinkedEntity
@@ -507,171 +76,20 @@ Note that certain longer field examples may be truncated for readability.
 ```
 {
 	"parentTitle": {
-		"recordId": "ErgKVmOjIOeiFEge88_z0Ow@19",
-		"name": "American Masters",
-		"websiteUris": [
-			"imdb.com/title/tt0364151"
+		"summary": "",
+		"image": "",
+		"images": [
+			{
+				"classifications": "",
+				"fingerprint": "",
+				"title": "",
+				"isCached": false,
+				"url": ""
+			}
 		],
-		"surfaceForm": "American Masters",
-		"position": "creativeWorkParentWork",
-		"type": "CreativeWork"
-	}
-}
-```
-### plotKeywords
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"plotKeywords": [
-		"music episode",
-		"song",
-		"singer"
-	]
-}
-```
-### plotSummary
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"plotSummary": "A profile of Canadian singer-songwriter Joni Mitchell, and how her music evolved from personal folk into pop, jazz and avant-garde."
-}
-```
-### podCategories
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"podCategories": ""
-}
-```
-### podDescription
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"podDescription": ""
-}
-```
-### posterImgLink
-  
-* **Type:** URL
-* **Example:**
-```
-{
-	"posterImgLink": ""
-}
-```
-### productionCompanies
-  
-* **Type:** LinkedEntity
-* **Example:**
-```
-{
-	"productionCompanies": [
-		{
-			"recordId": "ErgKVmOjIOeiFEge88_z0Ow@15",
-			"name": "Eagle Rock Entertainment",
-			"websiteUris": [
-				"imdb.com/company/co0015070"
-			],
-			"surfaceForm": "Eagle Rock Entertainment",
-			"position": "creativeWorkProductionOrganization",
-			"type": "Organization"
-		},
-		{
-			"recordId": "ErgKVmOjIOeiFEge88_z0Ow@16",
-			"name": "WNET Channel 13 New York",
-			"websiteUris": [
-				"imdb.com/company/co0037666"
-			],
-			"surfaceForm": "WNET Channel 13 New York",
-			"position": "creativeWorkProductionOrganization",
-			"type": "Organization"
-		}
-	]
-}
-```
-### releaseDate
-  
-* **Type:** DDate
-* **Example:**
-```
-{
-	"releaseDate": {
-		"str": "d2003-XX-XX",
-		"precision": 1,
-		"timestamp": 1041379200000
+		"types": "",
+		"diffbotUri": "",
+		"name": ""
 	}
 }
 ```
-### runtime
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"runtime": "92 min"
-}
-```
-### seasonNum
-  
-* **Type:** Integer
-* **Example:**
-```
-{
-	"seasonNum": 17
-}
-```
-### taglines
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"taglines": ""
-}
-```
-### trackPosition
-  
-* **Type:** Integer
-* **Example:**
-```
-{
-	"trackPosition": 0
-}
-```
-### videoMainLink
-  
-* **Type:** URL
-* **Example:**
-```
-{
-	"videoMainLink": ""
-}
-```
-### writers
-  
-* **Type:** LinkedEntity
-* **Example:**
-```
-{
-	"writers": [
-		{
-			"recordId": "ErgKVmOjIOeiFEge88_z0Ow@17",
-			"name": "Susan Lacy",
-			"websiteUris": [
-				"imdb.com/name/nm0480402"
-			],
-			"surfaceForm": "Susan Lacy",
-			"position": "creativeWorkWriter",
-			"type": "Person"
-		}
-	]
-}
-```
diff --git a/docs/kg-ont-diffbotentity.md b/docs/kg-ont-diffbotentity.md
index 7bc64037..b37346da 100644
--- a/docs/kg-ont-diffbotentity.md
+++ b/docs/kg-ont-diffbotentity.md
@@ -1,13 +1,20 @@
 ---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
 id: kg-ont-diffbotentity
 title: All
+generatedBy: generateOntology.js
 ---
 
 All Knowledge Graph entities will include the fields below, which are often generalized, linking, or metadata attributes common to all records. 
 
-See the left navigation panel for fields and attributes for specific entities,
+See the left navigation panel for fields and attributes of specific entities.
 
->New to the Diffbot Knowledge Graph? [Start here](dql-quickstart).
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
 
 ## All Fields
 * [allDescriptions](#alldescriptions) 
@@ -15,9 +22,9 @@ See the left navigation panel for fields and attributes for specific entities,
 * [allOriginHashes](#alloriginhashes) 
 * [allUriDetails](#alluridetails) 
 * [allUris](#alluris) 
-* [clusterWithOrigin](#clusterwithorigin) 
 * [crawlTimestamp](#crawltimestamp) 
 * [description](#description) 
+* [descriptors](#descriptors) 
 * [diffbotUri](#diffboturi) 
 * [id](#id) 
 * [image](#image) 
@@ -26,14 +33,18 @@ See the left navigation panel for fields and attributes for specific entities,
 * [name](#name) 
 * [nbIncomingEdges](#nbincomingedges) 
 * [nbOrigins](#nborigins) 
-* [nestedRecords](#nestedrecords) 
 * [nonCanonicalFacts](#noncanonicalfacts) 
 * [originDetails](#origindetails) 
 * [origins](#origins) 
-* [profileChangeProbability](#profilechangeprobability) 
 * [summary](#summary) 
 * [type](#type) 
 * [types](#types) 
+* [wikipediaPageviews](#wikipediapageviews) 
+* [wikipediaPageviewsGrowth](#wikipediapageviewsgrowth) 
+* [wikipediaPageviewsLastQuarter](#wikipediapageviewslastquarter) 
+* [wikipediaPageviewsLastQuarterGrowth](#wikipediapageviewslastquartergrowth) 
+* [wikipediaPageviewsLastYear](#wikipediapageviewslastyear) 
+* [wikipediaPageviewsLastYearGrowth](#wikipediapageviewslastyeargrowth) 
 
 ## All Field Details
 Note that certain longer field examples may be truncated for readability.
@@ -73,6 +84,9 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"allUriDetails": [
 		{
+			"domainMonthlyTrafficGrowth": "",
+			"domainMonthlyTraffic": 0,
+			"redirectsTo": "",
 			"nbFollowing": 0,
 			"uriType": "",
 			"verified": false,
@@ -94,15 +108,6 @@ Note that certain longer field examples may be truncated for readability.
 	"allUris": []
 }
 ```
-### clusterWithOrigin
-  
-* **Type:** String
-* **Example:**
-```
-{
-	"clusterWithOrigin": ""
-}
-```
 ### crawlTimestamp
   The default crawlTimestamp is the most recent date of all of the crawlTimestamps of the origins used to compute the Entity, returned as a UNIX time.
 * **Type:** Integer
@@ -121,6 +126,15 @@ Note that certain longer field examples may be truncated for readability.
 	"description": ""
 }
 ```
+### descriptors
+  A list of free-form keywords describing this entity
+* **Type:** String
+* **Example:**
+```
+{
+	"descriptors": ""
+}
+```
 ### diffbotUri
   diffbotUri is the URI an entity&#39;s  (URI), which is defined by appending the Diffbot ID to the URL https:&#x2F;&#x2F;diffbot.com&#x2F;entity&#x2F;. For example, Diffbot&#39;s entityID is CWSwJ_SWQPfqO3HQsxY4lGg and its DiffbotUri is https:&#x2F;&#x2F;diffbot.com&#x2F;entity&#x2F;CWSwJ_SWQPfqO3HQsxY4lGg
 * **Type:** URL
@@ -193,7 +207,7 @@ Note that certain longer field examples may be truncated for readability.
 }
 ```
 ### nbOrigins
-  Total number of origins in the field &#39;origins&#39;.
+  Total number of origins in the field &#39;origins&#39;. This field is only available in extended JSON mode.
 * **Type:** Integer
 * **Example:**
 ```
@@ -201,15 +215,6 @@ Note that certain longer field examples may be truncated for readability.
 	"nbOrigins": 0
 }
 ```
-### nestedRecords
-  
-* **Type:** DiffbotEntity
-* **Example:**
-```
-{
-	"nestedRecords": {}
-}
-```
 ### nonCanonicalFacts
   Enumerates all the non-canonical fields (i.e., those not defined in the ontology) that have a value for this entity. For instance, if &#39;numberOfChildren&#39; is listed in &#39;nonCanonicalFacts&#39; then the entity JSON will have the key &#39;numberOfChildren&#39; with an associated value. This field is only provided when the parameter nonCanonicalFacts&#x3D;1 is set. See: https:&#x2F;&#x2F;docs.diffbot.com&#x2F;kgapi
 * **Type:** String
@@ -220,7 +225,7 @@ Note that certain longer field examples may be truncated for readability.
 }
 ```
 ### originDetails
-  Additional information about origins listed in &#39;origins&#39;, including the latest time it was crawled.
+  Additional information about origins listed in &#39;origins&#39;, including the latest time it was crawled. This field is only available in extended JSON mode.
 * **Type:** OriginDetail
 * **Example:**
 ```
@@ -238,7 +243,7 @@ Note that certain longer field examples may be truncated for readability.
 }
 ```
 ### origins
-  An origin is a web address where Diffbot found one or more facts about an entity.
+  An origin is a web address where Diffbot found one or more facts about an entity. This field is only available in extended JSON mode.
 * **Type:** String
 * **Example:**
 ```
@@ -246,15 +251,6 @@ Note that certain longer field examples may be truncated for readability.
 	"origins": ""
 }
 ```
-### profileChangeProbability
-  For Diffbot&#39;s internal use only.
-* **Type:** Float
-* **Example:**
-```
-{
-	"profileChangeProbability": ""
-}
-```
 ### summary
   A short phrase designed to disambiguate entities with the same or similar name
 * **Type:** String
@@ -265,8 +261,8 @@ Note that certain longer field examples may be truncated for readability.
 }
 ```
 ### type
-  The main type of a Diffbot entity. Examples of type include Person, Organization, Article, Product.
-* **Type:** String
+  The top-level type of a Diffbot entity. Examples of type include Person, Organization, Article, Product.
+* **Type:** Type
 * **Example:**
 ```
 {
@@ -282,3 +278,57 @@ Note that certain longer field examples may be truncated for readability.
 	"types": ""
 }
 ```
+### wikipediaPageviews
+  The number of views of its Wikipedia page of the last month if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviews": 0
+}
+```
+### wikipediaPageviewsGrowth
+  The month over month growth of wikipediaPageviews, where we count the increment of the number of page views of the second to last (full) month, compared with that of the last (full) month. if today was Aug 16th, 2022, the last complete month is July. So it refers to the increment from June to July, i.e., ( f(July) - f(June) ) ÷ f(June) x 100%. The f(.) only counts the first 28 days of a month, to avoid fluctuations between 31-days months like Jan and 28(29)-days months like Feb.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsGrowth": ""
+}
+```
+### wikipediaPageviewsLastQuarter
+  The number of views of its Wikipedia page of the last quarter if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastQuarter": 0
+}
+```
+### wikipediaPageviewsLastQuarterGrowth
+  The quarter over quarter growth of wikipediaPageviews, where we count the increment of the number of page views of the second to last (full) quarter, compared with that of the last (full) quarter. If today was Aug 16th, 2022, the last complete quarter is Q2 (April, May, June). So it refers to the increment from Q1 to Q2, i.e., ( f(Q2) - f(Q1) ) ÷ f(Q1) x 100%.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastQuarterGrowth": ""
+}
+```
+### wikipediaPageviewsLastYear
+  The number of views of its Wikipedia page of the last year if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastYear": 0
+}
+```
+### wikipediaPageviewsLastYearGrowth
+  The year over year growth of wikipediaPageviews, where we count the monthly-rolling increment of the year before last than the last year. It today was Aug 16th, 2022, it is computed by comparing the numbers from Aug 2021 to July 2022 and from Aug 2020 to July 2021, i.e., ( f(Aug 2021 to July 2022) - f(Aug 2020 to July 2021) ) ÷ f(Aug 2020 to July 2021) x 100%.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastYearGrowth": ""
+}
+```
diff --git a/docs/kg-ont-discussion.md b/docs/kg-ont-discussion.md
index 1a7e4ef1..2bd885f8 100644
--- a/docs/kg-ont-discussion.md
+++ b/docs/kg-ont-discussion.md
@@ -1,30 +1,71 @@
 ---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
 id: kg-ont-discussion
 title: Discussion
+generatedBy: generateOntology.js
 ---
 
 The Discussion entity type encompasses forum and other similar discussions found throughout the web and known to the Knowledge Graph. 
 
 Note that fields are not guaranteed to exist in every entity record.
 
->New to the Diffbot Knowledge Graph? [Start here](dql-quickstart).
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
 
 ## Discussion Fields
+* [crawlTimestamp](#crawltimestamp) 
+* [diffbotUri](#diffboturi) 
+* [id](#id) 
 * [language](#language) 
 * [nextPage](#nextpage) 
 * [nextPages](#nextpages) 
 * [numPages](#numpages) 
 * [numParticipants](#numparticipants) 
 * [numPosts](#numposts) 
+* [pageUrl](#pageurl) 
 * [posts](#posts) 
 * [provider](#provider) 
+* [resolvedPageUrl](#resolvedpageurl) 
 * [rssUrl](#rssurl) 
 * [tags](#tags) 
 * [title](#title) 
+* [type](#type) 
+* [types](#types) 
 
 ## Discussion Field Details
 Note that certain longer field examples may be truncated for readability.
 
+### crawlTimestamp
+  Last time a site was crawled&#x2F;indexed
+* **Type:** Integer
+* **Example:**
+```
+{
+	"crawlTimestamp": 0
+}
+```
+### diffbotUri
+  diffbotUri is a combination of an entityID and a corresponding web address or uniform resource identifier (URI), which is defined by appending the entityID to the URL https:&#x2F;&#x2F;www.diffbot.com&#x2F;entity&#x2F;. For example, Diffbot&#39;s entityID is CWSwJ_SWQPfqO3HQsxY4lGg and its DiffbotUri is https:&#x2F;&#x2F;www.diffbot.com&#x2F;entity&#x2F;CWSwJ_SWQPfqO3HQsxY4lGg
+* **Type:** String
+* **Example:**
+```
+{
+	"diffbotUri": ""
+}
+```
+### id
+  Each entity in the Diffbot KnowledgeGraph (DKG) is identified by a unique identifier, an alphanumeric string like CWSwJ_SWQPfqO3HQsxY4lGg that uniquely identifies that entity. The id is directly derived from the most authoritative origin from the origins array.
+* **Type:** String
+* **Example:**
+```
+{
+	"id": ""
+}
+```
 ### language
   Refers to the language which a Discussion is written
 * **Type:** String
@@ -79,6 +120,15 @@ Note that certain longer field examples may be truncated for readability.
 	"numPosts": 0
 }
 ```
+### pageUrl
+  URL of submitted page &#x2F; page from which the entity is extracted
+* **Type:** String
+* **Example:**
+```
+{
+	"pageUrl": ""
+}
+```
 ### posts
   
 * **Type:** DiscussionPost
@@ -142,6 +192,15 @@ Note that certain longer field examples may be truncated for readability.
 	"provider": ""
 }
 ```
+### resolvedPageUrl
+  Returned if the pageUrl redirects to another URL
+* **Type:** String
+* **Example:**
+```
+{
+	"resolvedPageUrl": ""
+}
+```
 ### rssUrl
   
 * **Type:** String
@@ -178,3 +237,21 @@ Note that certain longer field examples may be truncated for readability.
 	"title": ""
 }
 ```
+### type
+  The top-level type of a Diffbot entity. Examples of type include Person, Organization, Article, Product.
+* **Type:** Type
+* **Example:**
+```
+{
+	"type": ""
+}
+```
+### types
+  There are tags.types which can only refer to dbpedia rdf types, while there are also the general DiffbotEntity types which is just an array of all the types an object belongs to. For instance a LocalBusiness would have &#x60;types:[&quot;Organization&quot;,&quot;LocalBusiness&quot;]&#x60; Finally, there are types that indicate a belonging to a subgroup such as business vs personal email address.
+* **Type:** String
+* **Example:**
+```
+{
+	"types": ""
+}
+```
diff --git a/docs/kg-ont-event.md b/docs/kg-ont-event.md
index 953e2682..c49876c9 100644
--- a/docs/kg-ont-event.md
+++ b/docs/kg-ont-event.md
@@ -1,32 +1,335 @@
 ---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
 id: kg-ont-event
 title: Event
+generatedBy: generateOntology.js
 ---
 
 The Event entity type encompasses webinars, meet ups, conferences, and other events known to the Knowledge Graph. 
 
 Note that fields are not guaranteed to exist in every entity record.
 
->New to the Diffbot Knowledge Graph? [Start here](dql-quickstart).
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
 
 ## Event Fields
+* [allDescriptions](#alldescriptions) 
+* [allNames](#allnames) 
+* [allOriginHashes](#alloriginhashes) 
+* [allUriDetails](#alluridetails) 
+* [allUris](#alluris) 
+* [categories](#categories) 
+* [crawlTimestamp](#crawltimestamp) 
+* [description](#description) 
+* [descriptors](#descriptors) 
+* [diffbotUri](#diffboturi) 
 * [endDateTime](#enddatetime) 
+* [humanLanguage](#humanlanguage) 
+* [id](#id) 
+* [image](#image) 
+* [images](#images) 
+* [importance](#importance) 
+* [location](#location) 
 * [locations](#locations) 
+* [name](#name) 
+* [nbIncomingEdges](#nbincomingedges) 
+* [nbOrigins](#nborigins) 
+* [nonCanonicalFacts](#noncanonicalfacts) 
+* [onlineLink](#onlinelink) 
+* [originDetails](#origindetails) 
+* [origins](#origins) 
+* [sponsors](#sponsors) 
 * [startDateTime](#startdatetime) 
+* [summary](#summary) 
+* [tags](#tags) 
+* [timezone](#timezone) 
+* [timezoneOffset](#timezoneoffset) 
+* [type](#type) 
+* [types](#types) 
+* [venue](#venue) 
+* [wikipediaPageviews](#wikipediapageviews) 
+* [wikipediaPageviewsGrowth](#wikipediapageviewsgrowth) 
+* [wikipediaPageviewsLastQuarter](#wikipediapageviewslastquarter) 
+* [wikipediaPageviewsLastQuarterGrowth](#wikipediapageviewslastquartergrowth) 
+* [wikipediaPageviewsLastYear](#wikipediapageviewslastyear) 
+* [wikipediaPageviewsLastYearGrowth](#wikipediapageviewslastyeargrowth) 
 
 ## Event Field Details
 Note that certain longer field examples may be truncated for readability.
 
+### allDescriptions
+  All descriptions found for this entity. For the best description, refer to the field &#39;description&#39;.
+* **Type:** String
+* **Example:**
+```
+{
+	"allDescriptions": [
+		"We’re thrilled to invite you to our Talent Connect Partnership Meet & Greet – a morning built for forging partnerships, opening doors to a pipeline of passionate, trained talent.\nWhy attend?\nPurpose‑driven venue. The Community Action Culinary Arts & Resource Center at 1906 Sherman Ave. in North Chicago, IL, exists to serve the community, help people and change lives Our work is deeply rooted in creating employment and career opportunities for local residents.\n What better place to dream up the future of your workforce?\nDiscover Talent Connect. Our Talent Connect employee referral service gives members access to a robust network of local talent and employment opportunities. It’s designed for businesses that want to connect with qualified candidates and for individuals eager to showcase their skills. At the Meet & Greet you’ll learn how this program can become a pipeline to your next star employee – or even your entire next team.\nForward‑thinking partnerships. We’re not just making introductions; we’re forging relationships built on shared goals.\nTime well spent. Breakfast starts at 7:30 AM; we are seeking your input about program successes and upcoming initiatives. We’ll wrap up with a pitch on how Talent Connect can support your hiring strategies and community engagement goals."
+	]
+}
+```
+### allNames
+  All names used, including nicknames, full names and transliterations to other languages.
+* **Type:** String
+* **Example:**
+```
+{
+	"allNames": [
+		"Talent Connect Partnership Meet & Greet"
+	]
+}
+```
+### allOriginHashes
+  For Diffbot&#39;s internal use only.
+* **Type:** String
+* **Example:**
+```
+{
+	"allOriginHashes": [
+		"MjgERJohOJaHe2p2YUXB3g"
+	]
+}
+```
+### allUriDetails
+  Additional information about each URI in &#39;allUris&#39;, which lists the URIs associated with this entity.
+* **Type:** UriDetails
+* **Example:**
+```
+{
+	"allUriDetails": [
+		{
+			"domainMonthlyTrafficGrowth": "",
+			"domainMonthlyTraffic": 0,
+			"redirectsTo": "",
+			"nbFollowing": 0,
+			"uriType": "",
+			"verified": false,
+			"nbLinkedAccounts": 0,
+			"nbFollowers": 0,
+			"httpCodeTimestamp": 0,
+			"httpCode": "",
+			"uri": ""
+		}
+	]
+}
+```
+### allUris
+  All URIs associated with an entity. A URI (uniform resource identifier) is a page on the web that describes an entity (e.g., an company&#39;s homepage or a person&#39;s social network profile).
+* **Type:** URL
+* **Example:**
+```
+{
+	"allUris": []
+}
+```
+### categories
+  Array of categories which represent the abstract subject of the entity
+* **Type:** KGCategory
+* **Example:**
+```
+{
+	"categories": [
+		{
+			"score": 1,
+			"name": "Social",
+			"id": "iabv2-1007"
+		},
+		{
+			"score": 0.985,
+			"name": "Business",
+			"id": "iabv2-53"
+		},
+		{
+			"score": 0.985,
+			"name": "Business and Finance",
+			"id": "iabv2-52"
+		}
+	]
+}
+```
+### crawlTimestamp
+  The default crawlTimestamp is the most recent date of all of the crawlTimestamps of the origins used to compute the Entity, returned as a UNIX time.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"crawlTimestamp": 1755011801
+}
+```
+### description
+  A few sentences describing an entity
+* **Type:** String
+* **Example:**
+```
+{
+	"description": "We’re thrilled to invite you to our Talent Connect Partnership Meet & Greet – a morning built for forging partnerships, opening doors to a pipeline of passionate, trained talent.\nWhy attend?\nPurpose‑driven venue. The Community Action Culinary Arts & Resource Center at 1906 Sherman Ave. in North Chicago, IL, exists to serve the community, help people and change lives Our work is deeply rooted in creating employment and career opportunities for local residents.\n What better place to dream up the future of your workforce?\nDiscover Talent Connect. Our Talent Connect employee referral service gives members access to a robust network of local talent and employment opportunities. It’s designed for businesses that want to connect with qualified candidates and for individuals eager to showcase their skills. At the Meet & Greet you’ll learn how this program can become a pipeline to your next star employee – or even your entire next team.\nForward‑thinking partnerships. We’re not just making introductions; we’re forging relationships built on shared goals.\nTime well spent. Breakfast starts at 7:30 AM; we are seeking your input about program successes and upcoming initiatives. We’ll wrap up with a pitch on how Talent Connect can support your hiring strategies and community engagement goals."
+}
+```
+### descriptors
+  A list of free-form keywords describing this entity
+* **Type:** String
+* **Example:**
+```
+{
+	"descriptors": ""
+}
+```
+### diffbotUri
+  diffbotUri is the URI an entity&#39;s  (URI), which is defined by appending the Diffbot ID to the URL https:&#x2F;&#x2F;diffbot.com&#x2F;entity&#x2F;. For example, Diffbot&#39;s entityID is CWSwJ_SWQPfqO3HQsxY4lGg and its DiffbotUri is https:&#x2F;&#x2F;diffbot.com&#x2F;entity&#x2F;CWSwJ_SWQPfqO3HQsxY4lGg
+* **Type:** URL
+* **Example:**
+```
+{
+	"diffbotUri": "http://diffbot.com/entity/EMjgERJohOJaHe2p2YUXB3g"
+}
+```
 ### endDateTime
-  
+  Event start date and time in GMT
 * **Type:** DDateTime
 * **Example:**
 ```
 {
 	"endDateTime": {
-		"str": "d2018-10-11T07:00",
+		"str": "d2025-08-25T13:30",
 		"precision": 4,
-		"timestamp": 1539241200000
+		"timestamp": 1756128600000
+	}
+}
+```
+### humanLanguage
+  Refers to the language in which the event is published
+* **Type:** Language
+* **Example:**
+```
+{
+	"humanLanguage": {}
+}
+```
+### id
+  An alphanumeric string like CWSwJ_SWQPfqO3HQsxY4lGg that uniquely identifies an entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"id": "EMjgERJohOJaHe2p2YUXB3g"
+}
+```
+### image
+  The main image used to represent the entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"image": "https://kg.diffbot.com/image/api/get?fetch=yes&urls=g%3Cj7P0SttAi.NxBvz.qNb%3DT1G%5C%3D%254%5B%25Ku%25X%3Dp%3Ar.PzDx%7C.sPd%25pU%3E%5B%7DTh%3F%25Mw%7BX1B_9%5Eo%3Fg%25MzDk%7DJxEWuVs7T%7D%25eB%5B%25CpwKXoOu%7ER.Ui%7B1%3AfxPq%261sCT%3BBl5IkO%25%3C%7Bl%3EU6Yb9g%26L1Yx%26Eh2Ypk0E%26%7EBV0w%3B%25l%5Bi%25J9Pav%25wNX9S%26umd%7BDtBWFpDYQJt8M0JAzZ%2Fr%5C5ZQgj%3BNdr"
+}
+```
+### images
+  The visual representation of an entity usually in the form of a png, jpeg, gif, or svg file.
+* **Type:** ImageField
+* **Example:**
+```
+{
+	"images": [
+		{
+			"naturalHeight": 470,
+			"width": 940,
+			"url": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0SttAi.NxBvz.qNb%3DT1G%5C%3D%254%5B%25Ku%25X%3Dp%3Ar.PzDx%7C.sPd%25pU%3E%5B%7DTh%3F%25Mw%7BX1B_9%5Eo%3Fg%25MzDk%7DJxEWuVs7T%7D%25eB%5B%25CpwKXoOu%7ER.Ui%7B1%3AfxPq%261sCT%3BBl5IkO%25%3C%7Bl%3EU6Yb9g%26L1Yx%26Eh2Ypk0E%26%7EBV0w%3B%25l%5Bi%25J9Pav%25wNX9S%26umd%7BDtBWFpDYQJt8M0JAzZ%2Fr%5C5ZQgj%3BNdr",
+			"naturalWidth": 940,
+			"primary": true,
+			"height": 470
+		}
+	]
+}
+```
+### importance
+  A number between 0 and 100 indicating how important or popular an entity is.
+* **Type:** Float
+* **Example:**
+```
+{
+	"importance": 4.49222993850708
+}
+```
+### location
+  The location of the event.
+* **Type:** Location
+* **Example:**
+```
+{
+	"location": {
+		"venue": "Get Directions",
+		"country": {
+			"summary": "Country located primarily in North America",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ",
+			"types": [
+				"Place",
+				"AdministrativeArea",
+				"Country"
+			],
+			"name": "United States",
+			"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
+			"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
+			"type": "Place"
+		},
+		"address": "Get Directions, 1906 Sherman Ave Sherman Avenue, North Chicago, Illinois",
+		"city": {
+			"summary": "City and suburb of Chicago, Illinois, USA",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FGvvO%3EqO7Rb_i%40OnQXXDr%40%5BuMxz%7D0Fh4%600IQBTi%7D%5D%3BG%5B%2FizHkHaxUy%7EZyIZudx%3Ae%2F%3FvBr7DADfv%3DqJPRQp7T%2FNe%3AYy.gHZ",
+			"types": [
+				"Place",
+				"AdministrativeArea",
+				"City"
+			],
+			"name": "North Chicago",
+			"diffbotUri": "http://diffbot.com/entity/EXsoILJt3O065Ir6QcM2xsA",
+			"targetDiffbotId": "EXsoILJt3O065Ir6QcM2xsA",
+			"type": "Place"
+		},
+		"street": "1906 Sherman Ave Sherman Avenue",
+		"metroArea": {
+			"summary": "Metropolitan area in the United States",
+			"types": [
+				"Place",
+				"AdministrativeArea"
+			],
+			"name": "Chicago metropolitan area",
+			"diffbotUri": "http://diffbot.com/entity/EDdaNkfPANReoJCWjJ4clcQ",
+			"targetDiffbotId": "EDdaNkfPANReoJCWjJ4clcQ",
+			"type": "Place"
+		},
+		"subregion": {
+			"summary": "County in Illinois, United States",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEP%3ErO%3CLr2YdMfAg%7EAy6UoKm7MyKm%7B%5Ex6%3C%2FZj%7D%3F%3CXjNt.M%7E%40",
+			"types": [
+				"Place",
+				"AdministrativeArea"
+			],
+			"name": "Lake County",
+			"diffbotUri": "http://diffbot.com/entity/EphQDa_57PBiOq3FIcVlb1g",
+			"targetDiffbotId": "EphQDa_57PBiOq3FIcVlb1g",
+			"type": "Place"
+		},
+		"latitude": 42.31783676147461,
+		"precision": 4.552231788635254,
+		"postalCode": "60064",
+		"region": {
+			"summary": "State of the United States of America",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FFvuu%3ExS%7DYb%3B%60zzfDb%7DGoJ.yZl",
+			"types": [
+				"Place",
+				"AdministrativeArea",
+				"Region"
+			],
+			"name": "Illinois",
+			"diffbotUri": "http://diffbot.com/entity/EbCHmKRdnPNWDRqTZHroFbA",
+			"targetDiffbotId": "EbCHmKRdnPNWDRqTZHroFbA",
+			"type": "Place"
+		},
+		"longitude": -87.86309814453125
 	}
 }
 ```
@@ -38,40 +341,339 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"locations": [
 		{
+			"venue": "Get Directions",
 			"country": {
+				"summary": "Country located primarily in North America",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ",
+				"types": [
+					"Place",
+					"AdministrativeArea",
+					"Country"
+				],
 				"name": "United States",
-				"surfaceForm": "United States"
+				"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
+				"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
+				"type": "Place"
 			},
-			"isCurrent": true,
-			"address": "Anaheim Convention Center, Anaheim, California, CA, USA",
+			"address": "Get Directions, 1906 Sherman Ave Sherman Avenue, North Chicago, Illinois",
 			"city": {
-				"name": "Anaheim",
-				"surfaceForm": "Anaheim"
+				"summary": "City and suburb of Chicago, Illinois, USA",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FGvvO%3EqO7Rb_i%40OnQXXDr%40%5BuMxz%7D0Fh4%600IQBTi%7D%5D%3BG%5B%2FizHkHaxUy%7EZyIZudx%3Ae%2F%3FvBr7DADfv%3DqJPRQp7T%2FNe%3AYy.gHZ",
+				"types": [
+					"Place",
+					"AdministrativeArea",
+					"City"
+				],
+				"name": "North Chicago",
+				"diffbotUri": "http://diffbot.com/entity/EXsoILJt3O065Ir6QcM2xsA",
+				"targetDiffbotId": "EXsoILJt3O065Ir6QcM2xsA",
+				"type": "Place"
+			},
+			"street": "1906 Sherman Ave Sherman Avenue",
+			"metroArea": {
+				"summary": "Metropolitan area in the United States",
+				"types": [
+					"Place",
+					"AdministrativeArea"
+				],
+				"name": "Chicago metropolitan area",
+				"diffbotUri": "http://diffbot.com/entity/EDdaNkfPANReoJCWjJ4clcQ",
+				"targetDiffbotId": "EDdaNkfPANReoJCWjJ4clcQ",
+				"type": "Place"
 			},
-			"street": "Anaheim Convention Center",
 			"subregion": {
-				"name": "California",
-				"surfaceForm": "California"
+				"summary": "County in Illinois, United States",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEP%3ErO%3CLr2YdMfAg%7EAy6UoKm7MyKm%7B%5Ex6%3C%2FZj%7D%3F%3CXjNt.M%7E%40",
+				"types": [
+					"Place",
+					"AdministrativeArea"
+				],
+				"name": "Lake County",
+				"diffbotUri": "http://diffbot.com/entity/EphQDa_57PBiOq3FIcVlb1g",
+				"targetDiffbotId": "EphQDa_57PBiOq3FIcVlb1g",
+				"type": "Place"
 			},
-			"surfaceForm": "Anaheim Convention Center, Anaheim, California, CA, USA",
+			"latitude": 42.31783676147461,
+			"precision": 4.552231788635254,
+			"postalCode": "60064",
 			"region": {
-				"name": "CA",
-				"surfaceForm": "CA"
-			}
+				"summary": "State of the United States of America",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FFvuu%3ExS%7DYb%3B%60zzfDb%7DGoJ.yZl",
+				"types": [
+					"Place",
+					"AdministrativeArea",
+					"Region"
+				],
+				"name": "Illinois",
+				"diffbotUri": "http://diffbot.com/entity/EbCHmKRdnPNWDRqTZHroFbA",
+				"targetDiffbotId": "EbCHmKRdnPNWDRqTZHroFbA",
+				"type": "Place"
+			},
+			"longitude": -87.86309814453125
 		}
 	]
 }
 ```
-### startDateTime
+### name
+  Primary text label for this entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"name": "Talent Connect Partnership Meet & Greet"
+}
+```
+### nbIncomingEdges
+  This is the number of edges in the Knowledge Graph that point to this entity. For example, the nbIncomingEdges field for Google is over 100,000. This number includes the number of people that work at google, the number of investors who invested in google, etc.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"nbIncomingEdges": 0
+}
+```
+### nbOrigins
+  Total number of origins in the field &#39;origins&#39;. This field is only available in extended JSON mode.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"nbOrigins": 1
+}
+```
+### nonCanonicalFacts
+  Enumerates all the non-canonical fields (i.e., those not defined in the ontology) that have a value for this entity. For instance, if &#39;numberOfChildren&#39; is listed in &#39;nonCanonicalFacts&#39; then the entity JSON will have the key &#39;numberOfChildren&#39; with an associated value. This field is only provided when the parameter nonCanonicalFacts&#x3D;1 is set. See: https:&#x2F;&#x2F;docs.diffbot.com&#x2F;kgapi
+* **Type:** String
+* **Example:**
+```
+{
+	"nonCanonicalFacts": ""
+}
+```
+### onlineLink
+  
+* **Type:** String
+* **Example:**
+```
+{
+	"onlineLink": ""
+}
+```
+### originDetails
+  Additional information about origins listed in &#39;origins&#39;, including the latest time it was crawled. This field is only available in extended JSON mode.
+* **Type:** OriginDetail
+* **Example:**
+```
+{
+	"originDetails": [
+		{
+			"crawledAt": {
+				"str": "",
+				"precision": 0,
+				"timestamp": 0
+			},
+			"origin": ""
+		}
+	]
+}
+```
+### origins
+  An origin is a web address where Diffbot found one or more facts about an entity. This field is only available in extended JSON mode.
+* **Type:** String
+* **Example:**
+```
+{
+	"origins": [
+		"eventbrite.com/e/talent-connect-partnership-meet-greet-tickets-1542472329259"
+	]
+}
+```
+### sponsors
   
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"sponsors": [
+		{
+			"summary": "",
+			"image": "",
+			"images": [
+				{
+					"classifications": "",
+					"fingerprint": "",
+					"title": "",
+					"isCached": false,
+					"url": ""
+				}
+			],
+			"types": "",
+			"diffbotUri": "",
+			"name": ""
+		}
+	]
+}
+```
+### startDateTime
+  Event start date and time in GMT
 * **Type:** DDateTime
 * **Example:**
 ```
 {
 	"startDateTime": {
-		"str": "d2018-10-09T07:00",
+		"str": "d2025-08-25T12:30",
 		"precision": 4,
-		"timestamp": 1539068400000
+		"timestamp": 1756125000000
 	}
 }
 ```
+### summary
+  A short phrase designed to disambiguate entities with the same or similar name
+* **Type:** String
+* **Example:**
+```
+{
+	"summary": ""
+}
+```
+### tags
+  Array of tags&#x2F;entities, generated from analysis of the extracted text and cross-referenced with DBpedia and other data sources. Language-specific tags will be returned if the source text is in English, Chinese, French, German, Spanish or Russian.
+* **Type:** KGTag
+* **Example:**
+```
+{
+	"tags": [
+		{
+			"score": 0.5921527743339539,
+			"sentiment": 0,
+			"count": 1,
+			"label": "North Chicago",
+			"uri": "https://diffbot.com/entity/EXsoILJt3O065Ir6QcM2xsA",
+			"rdfTypes": [
+				"http://dbpedia.org/ontology/Place",
+				"http://dbpedia.org/ontology/PopulatedPlace",
+				"http://dbpedia.org/ontology/Settlement",
+				"http://dbpedia.org/ontology/City"
+			]
+		},
+		{
+			"score": 0.4346528649330139,
+			"sentiment": 0.779,
+			"count": 1,
+			"label": "culinary art",
+			"uri": "https://diffbot.com/entity/Er6nY2WBwO_Gmo0M3loM7CQ",
+			"rdfTypes": [
+				"http://dbpedia.org/ontology/Skill"
+			]
+		},
+		{
+			"score": 0.3224407732486725,
+			"sentiment": 0.79,
+			"count": 1,
+			"label": "partnership",
+			"uri": "https://diffbot.com/entity/E5flv0o6_OZqHZOKG5q2WyA"
+		}
+	]
+}
+```
+### timezone
+  IANA Timezone
+* **Type:** String
+* **Example:**
+```
+{
+	"timezone": ""
+}
+```
+### timezoneOffset
+  Timezone offset from GMT
+* **Type:** String
+* **Example:**
+```
+{
+	"timezoneOffset": "-05:00"
+}
+```
+### type
+  The top-level type of a Diffbot entity. Examples of type include Person, Organization, Article, Product.
+* **Type:** Type
+* **Example:**
+```
+{
+	"type": "Event"
+}
+```
+### types
+  All types of a Diffbot entity, including the value of the field &#39;type&#39;.
+* **Type:** String
+* **Example:**
+```
+{
+	"types": [
+		"Event"
+	]
+}
+```
+### venue
+  
+* **Type:** String
+* **Example:**
+```
+{
+	"venue": "Get Directions"
+}
+```
+### wikipediaPageviews
+  The number of views of its Wikipedia page of the last month if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviews": 0
+}
+```
+### wikipediaPageviewsGrowth
+  The month over month growth of wikipediaPageviews, where we count the increment of the number of page views of the second to last (full) month, compared with that of the last (full) month. if today was Aug 16th, 2022, the last complete month is July. So it refers to the increment from June to July, i.e., ( f(July) - f(June) ) ÷ f(June) x 100%. The f(.) only counts the first 28 days of a month, to avoid fluctuations between 31-days months like Jan and 28(29)-days months like Feb.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsGrowth": ""
+}
+```
+### wikipediaPageviewsLastQuarter
+  The number of views of its Wikipedia page of the last quarter if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastQuarter": 0
+}
+```
+### wikipediaPageviewsLastQuarterGrowth
+  The quarter over quarter growth of wikipediaPageviews, where we count the increment of the number of page views of the second to last (full) quarter, compared with that of the last (full) quarter. If today was Aug 16th, 2022, the last complete quarter is Q2 (April, May, June). So it refers to the increment from Q1 to Q2, i.e., ( f(Q2) - f(Q1) ) ÷ f(Q1) x 100%.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastQuarterGrowth": ""
+}
+```
+### wikipediaPageviewsLastYear
+  The number of views of its Wikipedia page of the last year if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastYear": 0
+}
+```
+### wikipediaPageviewsLastYearGrowth
+  The year over year growth of wikipediaPageviews, where we count the monthly-rolling increment of the year before last than the last year. It today was Aug 16th, 2022, it is computed by comparing the numbers from Aug 2021 to July 2022 and from Aug 2020 to July 2021, i.e., ( f(Aug 2021 to July 2022) - f(Aug 2020 to July 2021) ) ÷ f(Aug 2020 to July 2021) x 100%.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastYearGrowth": ""
+}
+```
diff --git a/docs/kg-ont-faq.md b/docs/kg-ont-faq.md
new file mode 100644
index 00000000..c1f7de6f
--- /dev/null
+++ b/docs/kg-ont-faq.md
@@ -0,0 +1,54 @@
+---
+id: kg-ont-faq
+title: Faq
+generatedBy: generateOntology.js
+---
+
+The FAQ entity type is a specialized list of questions and corresponding answers. 
+
+Note that fields are not guaranteed to exist in every entity record.
+
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
+
+## Faq Fields
+* [faqs](#faqs) 
+* [title](#title) 
+
+## Faq Field Details
+Note that certain longer field examples may be truncated for readability.
+
+### faqs
+  List of the faqs
+* **Type:** FaqQnA
+* **Example:**
+```
+{
+	"faqs": [
+		{
+			"q": "How is Zika virus disease treated?",
+			"a": "Revised Zika virus country classification scheme"
+		},
+		{
+			"q": "How was the Zika virus country classification scheme developed?",
+			"a": "Zika and neurological complications"
+		},
+		{
+			"q": "Are there other explanations for microcephaly and Guillain-Barré syndrome?",
+			"a": "Mosquitoes transmitting Zika virus"
+		}
+	]
+}
+```
+### title
+  Faq title
+* **Type:** String
+* **Example:**
+```
+{
+	"title": "Zika virus and complications: Questions and answers"
+}
+```
diff --git a/docs/kg-ont-image.md b/docs/kg-ont-image.md
index bd545841..1de11576 100644
--- a/docs/kg-ont-image.md
+++ b/docs/kg-ont-image.md
@@ -1,25 +1,39 @@
 ---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
 id: kg-ont-image
 title: Image
+generatedBy: generateOntology.js
 ---
 
 The Image entity type encompasses images found throughout the web and known to the Knowledge Graph. 
 
 Note that fields are not guaranteed to exist in every entity record.
 
->New to the Diffbot Knowledge Graph? [Start here](dql-quickstart).
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
 
 ## Image Fields
 * [anchorUrl](#anchorurl) 
 * [breadcrumb](#breadcrumb) 
+* [crawlTimestamp](#crawltimestamp) 
+* [diffbotUri](#diffboturi) 
 * [displayHeight](#displayheight) 
 * [displayWidth](#displaywidth) 
+* [id](#id) 
 * [language](#language) 
 * [links](#links) 
 * [naturalHeight](#naturalheight) 
 * [naturalWidth](#naturalwidth) 
+* [pageUrl](#pageurl) 
+* [resolvedPageUrl](#resolvedpageurl) 
 * [tags](#tags) 
 * [title](#title) 
+* [type](#type) 
+* [types](#types) 
 * [url](#url) 
 * [xpath](#xpath) 
 
@@ -49,6 +63,24 @@ Note that certain longer field examples may be truncated for readability.
 	]
 }
 ```
+### crawlTimestamp
+  Last time a site was crawled&#x2F;indexed
+* **Type:** Integer
+* **Example:**
+```
+{
+	"crawlTimestamp": 1700198633
+}
+```
+### diffbotUri
+  diffbotUri is a combination of an entityID and a corresponding web address or uniform resource identifier (URI), which is defined by appending the entityID to the URL https:&#x2F;&#x2F;www.diffbot.com&#x2F;entity&#x2F;. For example, Diffbot&#39;s entityID is CWSwJ_SWQPfqO3HQsxY4lGg and its DiffbotUri is https:&#x2F;&#x2F;www.diffbot.com&#x2F;entity&#x2F;CWSwJ_SWQPfqO3HQsxY4lGg
+* **Type:** String
+* **Example:**
+```
+{
+	"diffbotUri": "http://diffbot.com/entity/IMG62073555748"
+}
+```
 ### displayHeight
   Height of image as presented in the browser (and as sized via browser&#x2F;CSS, if resized)
 * **Type:** Integer
@@ -67,6 +99,15 @@ Note that certain longer field examples may be truncated for readability.
 	"displayWidth": 0
 }
 ```
+### id
+  Each entity in the Diffbot KnowledgeGraph (DKG) is identified by a unique identifier, an alphanumeric string like CWSwJ_SWQPfqO3HQsxY4lGg that uniquely identifies that entity. The id is directly derived from the most authoritative origin from the origins array.
+* **Type:** String
+* **Example:**
+```
+{
+	"id": "IMG62073555748"
+}
+```
 ### language
   
 * **Type:** String
@@ -91,7 +132,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"naturalHeight": 1056
+	"naturalHeight": 3417
 }
 ```
 ### naturalWidth
@@ -100,7 +141,25 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"naturalWidth": 1176
+	"naturalWidth": 3418
+}
+```
+### pageUrl
+  URL of submitted page &#x2F; page from which the entity is extracted
+* **Type:** String
+* **Example:**
+```
+{
+	"pageUrl": ""
+}
+```
+### resolvedPageUrl
+  Returned if the pageUrl redirects to another URL
+* **Type:** String
+* **Example:**
+```
+{
+	"resolvedPageUrl": ""
 }
 ```
 ### tags
@@ -127,7 +186,27 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"title": "A visualization of the Knowledge Graph"
+	"title": "Mike Tung of Diffbot"
+}
+```
+### type
+  The top-level type of a Diffbot entity. Examples of type include Person, Organization, Article, Product.
+* **Type:** Type
+* **Example:**
+```
+{
+	"type": "Image"
+}
+```
+### types
+  There are tags.types which can only refer to dbpedia rdf types, while there are also the general DiffbotEntity types which is just an array of all the types an object belongs to. For instance a LocalBusiness would have &#x60;types:[&quot;Organization&quot;,&quot;LocalBusiness&quot;]&#x60; Finally, there are types that indicate a belonging to a subgroup such as business vs personal email address.
+* **Type:** String
+* **Example:**
+```
+{
+	"types": [
+		"Image"
+	]
 }
 ```
 ### url
@@ -136,7 +215,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"url": "https://cdn-images-1.medium.com/max/1600/1*sYLBdAl7pP2krTspeWZosA.png"
+	"url": "https://imageio.forbes.com/specials-images/imageserve/5cd587b85ea6490008c81044/Mike-Tung-of-Diffbot/0x0.jpg?format=jpg&crop=3418,3417,x470,y0,safe&height=3417&width=3418"
 }
 ```
 ### xpath
diff --git a/docs/kg-ont-job.md b/docs/kg-ont-job.md
new file mode 100644
index 00000000..b842f87e
--- /dev/null
+++ b/docs/kg-ont-job.md
@@ -0,0 +1,81 @@
+---
+id: kg-ont-job
+title: Job
+generatedBy: generateOntology.js
+---
+
+The Job entity type represents roles of employment found throughout the web and known to the Knowledge Graph. 
+
+Note that fields are not guaranteed to exist in every entity record.
+
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
+
+## Job Fields
+* [company](#company) 
+* [humanLanguage](#humanlanguage) 
+* [requirements](#requirements) 
+* [tasks](#tasks) 
+* [text](#text) 
+* [title](#title) 
+
+## Job Field Details
+Note that certain longer field examples may be truncated for readability.
+
+### company
+  
+* **Type:** String
+* **Example:**
+```
+{
+	"company": ""
+}
+```
+### humanLanguage
+  Refers to the humanLanguage in which a Job is written
+* **Type:** String
+* **Example:**
+```
+{
+	"humanLanguage": ""
+}
+```
+### requirements
+  Required skills&#x2F;experiences for the job
+* **Type:** String
+* **Example:**
+```
+{
+	"requirements": ""
+}
+```
+### tasks
+  List of the job&#39;s tasks and responsibilities
+* **Type:** String
+* **Example:**
+```
+{
+	"tasks": ""
+}
+```
+### text
+  
+* **Type:** String
+* **Example:**
+```
+{
+	"text": ""
+}
+```
+### title
+  Job title
+* **Type:** String
+* **Example:**
+```
+{
+	"title": ""
+}
+```
diff --git a/docs/kg-ont-organization.md b/docs/kg-ont-organization.md
index 5889ee0b..0eb8fe35 100644
--- a/docs/kg-ont-organization.md
+++ b/docs/kg-ont-organization.md
@@ -1,37 +1,66 @@
 ---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
 id: kg-ont-organization
 title: Organization
+generatedBy: generateOntology.js
 ---
 
 The organization entity type encompasses corporations, local businesses, non-profits, and other organizations known to the Knowledge Graph. 
 
 Note that fields are not guaranteed to exist in every entity record.
 
->New to the Diffbot Knowledge Graph? [Start here](dql-quickstart).
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
 
 ## Organization Fields
+* [abnNumbers](#abnnumbers) 
+* [acnNumbers](#acnnumbers) 
 * [acquiredBy](#acquiredby) 
+* [allDescriptions](#alldescriptions) 
+* [allNames](#allnames) 
+* [allOriginHashes](#alloriginhashes) 
+* [allUriDetails](#alluridetails) 
+* [allUris](#alluris) 
 * [angellistUri](#angellisturi) 
 * [anzSicClassification](#anzsicclassification) 
 * [blogUri](#bloguri) 
 * [boardMembers](#boardmembers) 
-* [brands](#brands) 
+* [canadianBusinessNumbers](#canadianbusinessnumbers) 
 * [capitalization](#capitalization) 
 * [categories](#categories) 
 * [ceo](#ceo) 
+* [chineseSocialCreditCodes](#chinesesocialcreditcodes) 
 * [companiesHouseIds](#companieshouseids) 
+* [competitors](#competitors) 
+* [crawlTimestamp](#crawltimestamp) 
 * [crunchbaseUri](#crunchbaseuri) 
+* [cuitNumbers](#cuitnumbers) 
+* [customers](#customers) 
+* [description](#description) 
 * [descriptors](#descriptors) 
+* [diffbotUri](#diffboturi) 
+* [edrpouNumbers](#edrpounumbers) 
+* [emailAddresses](#emailaddresses) 
+* [employeeCategories](#employeecategories) 
 * [facebookUri](#facebookuri) 
 * [founders](#founders) 
 * [foundingDate](#foundingdate) 
+* [fullName](#fullname) 
 * [githubUri](#githuburi) 
 * [googlePlusUri](#googleplusuri) 
 * [guiNumbers](#guinumbers) 
+* [hasRemoteInternationalEmployees](#hasremoteinternationalemployees) 
 * [homepageUri](#homepageuri) 
 * [iSicClassification](#isicclassification) 
+* [id](#id) 
+* [image](#image) 
+* [images](#images) 
+* [importance](#importance) 
 * [indianCorporateIdentityNumbers](#indiancorporateidentitynumbers) 
-* [industries](#industries) 
 * [investments](#investments) 
 * [ipo](#ipo) 
 * [irsEmployerIdentificationNumbers](#irsemployeridentificationnumbers) 
@@ -39,8 +68,10 @@ Note that fields are not guaranteed to exist in every entity record.
 * [isDissolved](#isdissolved) 
 * [isNonProfit](#isnonprofit) 
 * [isPublic](#ispublic) 
+* [israeliCompanyNumbers](#israelicompanynumbers) 
 * [japaneseCorporateNumbers](#japanesecorporatenumbers) 
-* [leadership](#leadership) 
+* [kvedClassification](#kvedclassification) 
+* [legalEntities](#legalentities) 
 * [linkedInUri](#linkedinuri) 
 * [location](#location) 
 * [locations](#locations) 
@@ -48,29 +79,40 @@ Note that fields are not guaranteed to exist in every entity record.
 * [mccClassification](#mccclassification) 
 * [mccCode](#mcccode) 
 * [mccCodeDescription](#mcccodedescription) 
+* [monthlyTraffic](#monthlytraffic) 
+* [monthlyTrafficGrowth](#monthlytrafficgrowth) 
 * [motto](#motto) 
 * [naceClassification](#naceclassification) 
 * [nafClassification](#nafclassification) 
 * [naicsClassification](#naicsclassification) 
+* [naicsClassification2017](#naicsclassification2017) 
+* [name](#name) 
 * [nbActiveEmployeeEdges](#nbactiveemployeeedges) 
 * [nbEmployeeRanges](#nbemployeeranges) 
 * [nbEmployees](#nbemployees) 
 * [nbEmployeesMax](#nbemployeesmax) 
 * [nbEmployeesMin](#nbemployeesmin) 
-* [nbEmployeesOnLinkedIn](#nbemployeesonlinkedin) 
-* [nbEmployeesOnLinkedInOverTime](#nbemployeesonlinkedinovertime) 
+* [nbIncomingEdges](#nbincomingedges) 
 * [nbLocations](#nblocations) 
+* [nbOrigins](#nborigins) 
 * [nbUniqueInvestors](#nbuniqueinvestors) 
+* [nonCanonicalFacts](#noncanonicalfacts) 
 * [norwegianOrganizationNumbers](#norwegianorganizationnumbers) 
+* [npiNumbers](#npinumbers) 
 * [okvedClassification](#okvedclassification) 
+* [originDetails](#origindetails) 
+* [origins](#origins) 
 * [parentCompany](#parentcompany) 
+* [partnerships](#partnerships) 
 * [phoneNumbers](#phonenumbers) 
 * [predecessors](#predecessors) 
 * [quarterlyRevenues](#quarterlyrevenues) 
+* [remoteScore](#remotescore) 
 * [revenue](#revenue) 
 * [russianTaxpayerIdentificationNumbers](#russiantaxpayeridentificationnumbers) 
 * [secCentralIndexKeys](#seccentralindexkeys) 
 * [secForms](#secforms) 
+* [sepaIds](#sepaids) 
 * [sicClassification](#sicclassification) 
 * [sicCode](#siccode) 
 * [sicCodeDescription](#siccodedescription) 
@@ -79,27 +121,73 @@ Note that fields are not guaranteed to exist in every entity record.
 * [stock](#stock) 
 * [subsidiaries](#subsidiaries) 
 * [successors](#successors) 
+* [summary](#summary) 
+* [suppliers](#suppliers) 
 * [technographics](#technographics) 
+* [thaiTaxpayerIds](#thaitaxpayerids) 
 * [totalInvestment](#totalinvestment) 
+* [tsicClassification](#tsicclassification) 
 * [twitterUri](#twitteruri) 
+* [type](#type) 
+* [types](#types) 
+* [uenNumbers](#uennumbers) 
 * [ukSicClassification](#uksicclassification) 
+* [ultimateParent](#ultimateparent) 
 * [vatIdentificationNumbers](#vatidentificationnumbers) 
+* [wikipediaPageviews](#wikipediapageviews) 
+* [wikipediaPageviewsGrowth](#wikipediapageviewsgrowth) 
+* [wikipediaPageviewsLastQuarter](#wikipediapageviewslastquarter) 
+* [wikipediaPageviewsLastQuarterGrowth](#wikipediapageviewslastquartergrowth) 
+* [wikipediaPageviewsLastYear](#wikipediapageviewslastyear) 
+* [wikipediaPageviewsLastYearGrowth](#wikipediapageviewslastyeargrowth) 
 * [wikipediaUri](#wikipediauri) 
 * [yearlyRevenues](#yearlyrevenues) 
 
 ## Organization Field Details
 Note that certain longer field examples may be truncated for readability.
 
+### abnNumbers
+  Australian Business Number (ABN) is a unique identifier provided by Australian Business Register (ABR).
+* **Type:** String
+* **Example:**
+```
+{
+	"abnNumbers": [
+		"46610921849"
+	]
+}
+```
+### acnNumbers
+  Australian Company Number (ACN) is a unique identifier given to all Australian companies.
+* **Type:** String
+* **Example:**
+```
+{
+	"acnNumbers": [
+		"610921849"
+	]
+}
+```
 ### acquiredBy
   The organization that has most recently acquired this organization.
-* **Type:** LinkedEntity
+* **Type:** AcquiredBy
 * **Example:**
 ```
 {
 	"acquiredBy": [
 		{
+			"date": {
+				"str": "",
+				"precision": 0,
+				"timestamp": 0
+			},
 			"summary": "",
 			"image": "",
+			"amount": {
+				"currency": "",
+				"value": ""
+			},
+			"isCurrent": false,
 			"images": [
 				{
 					"classifications": "",
@@ -110,22 +198,94 @@ Note that certain longer field examples may be truncated for readability.
 				}
 			],
 			"types": "",
-			"websiteUris": "",
 			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
+			"name": ""
+		}
+	]
+}
+```
+### allDescriptions
+  All descriptions found for this entity. For the best description, refer to the field &#39;description&#39;.
+* **Type:** String
+* **Example:**
+```
+{
+	"allDescriptions": [
+		"IBM is a leading cloud platform and cognitive solutions company. Founded in 1911, it is the largest technology and consulting employer in the world.",
+		"IBM Global Financing offers loans, leasing and IT financing Payment solutions.",
+		"IBM is an IT technology and consulting firm providing computer hardware, software, infrastructure, and hosting services."
+	]
+}
+```
+### allNames
+  All names used, including nicknames, full names and transliterations to other languages.
+* **Type:** String
+* **Example:**
+```
+{
+	"allNames": [
+		"IBM",
+		"IBM India Private Limited",
+		"IBM India"
+	]
+}
+```
+### allOriginHashes
+  For Diffbot&#39;s internal use only.
+* **Type:** String
+* **Example:**
+```
+{
+	"allOriginHashes": [
+		"eKPD0JbzMCKSlCT_lDiuIQ",
+		"DV7YS20lMU2ibHgiwW7cfA",
+		"IPiXHBOjO_6L9CG9F_NPeg"
+	]
+}
+```
+### allUriDetails
+  Additional information about each URI in &#39;allUris&#39;, which lists the URIs associated with this entity.
+* **Type:** UriDetails
+* **Example:**
+```
+{
+	"allUriDetails": [
+		{
+			"domainMonthlyTrafficGrowth": "",
+			"domainMonthlyTraffic": 0,
+			"redirectsTo": "",
+			"nbFollowing": 0,
+			"uriType": "",
+			"verified": false,
+			"nbLinkedAccounts": 0,
+			"nbFollowers": 0,
+			"httpCodeTimestamp": 0,
+			"httpCode": "",
+			"uri": ""
 		}
 	]
 }
 ```
+### allUris
+  All URIs associated with an entity. A URI (uniform resource identifier) is a page on the web that describes an entity (e.g., an company&#39;s homepage or a person&#39;s social network profile).
+* **Type:** URL
+* **Example:**
+```
+{
+	"allUris": [
+		"connectonline.asic.gov.au/RegistrySearch/faces/landing/panelSearch.jspx?searchType=OrgAndBusNm&searchText=610921849",
+		"annuaire-entreprises.data.gouv.fr/entreprise/890677800",
+		"data.gov.in/catalog/company-master-data/U30007KA1991PLC012619"
+	]
+}
+```
 ### angellistUri
   Link to the Angel List profile of this  entity
 * **Type:** URL
 * **Example:**
 ```
 {
-	"angellistUri": "angel.co/ibm"
+	"angellistUri": "angel.co/ibm-india-1"
 }
 ```
 ### anzSicClassification
@@ -137,8 +297,10 @@ Note that certain longer field examples may be truncated for readability.
 	"anzSicClassification": [
 		{
 			"code": "",
+			"level": 0,
 			"isPrimary": false,
 			"name": "",
+			"diffbotUri": "",
 			"version": ""
 		}
 	]
@@ -162,53 +324,49 @@ Note that certain longer field examples may be truncated for readability.
 	"boardMembers": [
 		{
 			"summary": "Indian American business executive and CEO of IBM",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St%7D9u.LnOv%7BI%7C%40g7.pBYINs%3Ff%7CGZ7jr-tGZhWf%3DK%2FOvy%5Bp%3CSKbs8i%7CEyNzC%60%3C_s8m5LcwEg%3CryObFQxFtEU3Cl%7DQ.I%5Do",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7guSXzAoBWu.x0KwLZrUn.%5B%3CR0Aa4Hwygr9m6W%3Exl5G%60BkxmPGd5%5Bg%7BE%3DJm%40gp7oEL8d7PC%28Fk1%601%3CT%29.o%3Ec",
 			"types": [
 				"Person"
 			],
 			"name": "Arvind Krishna",
 			"diffbotUri": "http://diffbot.com/entity/E2w9R5RLuMCSUb511otaM-Q",
-			"targetDiffbotUri": "http://diffbot.com/entity/E2w9R5RLuMCSUb511otaM-Q",
 			"targetDiffbotId": "E2w9R5RLuMCSUb511otaM-Q",
-			"surfaceForm": "Arvind Krishna",
 			"type": "Person"
 		},
 		{
-			"summary": "American business executive",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St%7D9u.LnOv%7BI%7C%40g7.pBYINs%3Ff%7CGZ7jr-tGZhWf%3DK%2FOvy%5Bp%3CSKbs8i%7CEyNzC%60%3B%5Bv%3Ci6Lc%7Bhs%3Ac5Ii%40W%7DVjN%5D4bnrC.I%5Do",
+			"summary": "American businessman & politician (born 1960)",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0SttAc%3ANu.d9U%7CB%5DpM08.%7DZnIa6%40_%3Bv2FpDLhawxEr-%5BuTpJZ%40-r%3Ec2Jh9e%3EN7Zv%3De%3DNdGkxHRsYU2qfV3MD2%3B2GcA%3FP%3Dil2gIG%7DIwIY.%3Aan",
 			"types": [
-				"Person"
+				"Person",
+				"PersonInvestor"
 			],
-			"name": "Ginni Rometty",
-			"diffbotUri": "http://diffbot.com/entity/EFCXA8DGjPMq5oTjl9RESEw",
-			"targetDiffbotUri": "http://diffbot.com/entity/EFCXA8DGjPMq5oTjl9RESEw",
-			"targetDiffbotId": "EFCXA8DGjPMq5oTjl9RESEw",
-			"surfaceForm": "Ginni Rometty",
+			"name": "Gary Cohn",
+			"diffbotUri": "http://diffbot.com/entity/EpEweymvaM0ug7Y-pCJBB3w",
+			"targetDiffbotId": "EpEweymvaM0ug7Y-pCJBB3w",
 			"type": "Person"
 		},
 		{
-			"summary": "American banker",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FjvIs%3ElO%3Efb_i3OY9mnzk%3EVuRf7C_H%5D%7BQpkQGN%281n%3CSl%3F_%29.xGV",
+			"summary": "Businessperson and corporate director; former chair and CEO, Johnson & Johnson",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0SttAc%3ANu.d9U%7CB%5DpM08.%7DZnIa6%40_%3Bv2FpDLhawxEr-%5BuTpJZ%40-r%3Ec2Jh9e%3EN7Zv%3De%3DMeCdxCpt8Q0uiU%7D2I%7E%3C%5Dwa%3AZuni%3FSfug1xwLZ.%3Aan",
 			"types": [
-				"Person"
+				"Person",
+				"PersonInvestor"
 			],
-			"name": "Gary Cohn",
-			"diffbotUri": "http://diffbot.com/entity/EpEweymvaM0ug7Y-pCJBB3w",
-			"targetDiffbotUri": "http://diffbot.com/entity/EpEweymvaM0ug7Y-pCJBB3w",
-			"targetDiffbotId": "EpEweymvaM0ug7Y-pCJBB3w",
-			"surfaceForm": "Gary Cohn",
+			"name": "Alex Gorsky",
+			"diffbotUri": "http://diffbot.com/entity/Ee_LAfNCLMK-VpvaJV4xpAA",
+			"targetDiffbotId": "Ee_LAfNCLMK-VpvaJV4xpAA",
 			"type": "Person"
 		}
 	]
 }
 ```
-### brands
-  Brands of an organization.
+### canadianBusinessNumbers
+  Canadian business number is an identifier given to all businesses in Canada.
 * **Type:** String
 * **Example:**
 ```
 {
-	"brands": ""
+	"canadianBusinessNumbers": ""
 }
 ```
 ### capitalization
@@ -219,13 +377,13 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"capitalization": {
 		"currency": "USD",
-		"value": 112935797000
+		"value": 227430350848
 	}
 }
 ```
 ### categories
   
-* **Type:** LinkedEntity
+* **Type:** LinkedCategory
 * **Example:**
 ```
 {
@@ -233,38 +391,38 @@ Note that certain longer field examples may be truncated for readability.
 		{
 			"types": [
 				"Intangible",
-				"IndustryCategory"
+				"OrganizationCategory"
 			],
-			"name": "Electronic Products Manufacturers",
-			"diffbotUri": "http://diffbot.com/entity/EUNd__O4zMNW81lAXNK2GNw",
-			"targetDiffbotUri": "http://diffbot.com/entity/EUNd__O4zMNW81lAXNK2GNw",
-			"targetDiffbotId": "EUNd__O4zMNW81lAXNK2GNw",
-			"surfaceForm": "Electronic Products Manufacturers",
-			"type": "IndustryCategory"
+			"level": 3,
+			"isPrimary": true,
+			"name": "Software As A Service Companies",
+			"diffbotUri": "http://diffbot.com/entity/EbdcyFE5NPjCPeXs1vyF_0w",
+			"targetDiffbotId": "EbdcyFE5NPjCPeXs1vyF_0w",
+			"type": "OrganizationCategory"
 		},
 		{
 			"types": [
 				"Intangible",
-				"IndustryCategory"
+				"OrganizationCategory"
 			],
-			"name": "Display Technology Companies",
-			"diffbotUri": "http://diffbot.com/entity/EX8GX-IaIP2Oi0rsYy_Bqfw",
-			"targetDiffbotUri": "http://diffbot.com/entity/EX8GX-IaIP2Oi0rsYy_Bqfw",
-			"targetDiffbotId": "EX8GX-IaIP2Oi0rsYy_Bqfw",
-			"surfaceForm": "Display Technology Companies",
-			"type": "IndustryCategory"
+			"level": 2,
+			"isPrimary": true,
+			"name": "Software Companies",
+			"diffbotUri": "http://diffbot.com/entity/EhbXSjlcgNVa4-JzwAvA7gQ",
+			"targetDiffbotId": "EhbXSjlcgNVa4-JzwAvA7gQ",
+			"type": "OrganizationCategory"
 		},
 		{
 			"types": [
 				"Intangible",
-				"IndustryCategory"
+				"OrganizationCategory"
 			],
-			"name": "Computer Hardware Companies",
-			"diffbotUri": "http://diffbot.com/entity/EqFeVtLRWOUqTdzVhcYwBBQ",
-			"targetDiffbotUri": "http://diffbot.com/entity/EqFeVtLRWOUqTdzVhcYwBBQ",
-			"targetDiffbotId": "EqFeVtLRWOUqTdzVhcYwBBQ",
-			"surfaceForm": "Computer Hardware Companies",
-			"type": "IndustryCategory"
+			"level": 1,
+			"isPrimary": true,
+			"name": "Technology Companies",
+			"diffbotUri": "http://diffbot.com/entity/EGkMjRFN1PdC0t0QPTVncVg",
+			"targetDiffbotId": "EGkMjRFN1PdC0t0QPTVncVg",
+			"type": "OrganizationCategory"
 		}
 	]
 }
@@ -277,19 +435,26 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"ceo": {
 		"summary": "Indian American business executive and CEO of IBM",
-		"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St%7D9u.LnOv%7BI%7C%40g7.pBYINs%3Ff%7CGZ7jr-tGZhWf%3DK%2FOvy%5Bp%3CSKbs8i%7CEyNzC%60%3C_s8m5LcwEg%3CryObFQxFtEU3Cl%7DQ.I%5Do",
+		"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7guSXzAoBWu.x0KwLZrUn.%5B%3CR0Aa4Hwygr9m6W%3Exl5G%60BkxmPGd5%5Bg%7BE%3DJm%40gp7oEL8d7PC%28Fk1%601%3CT%29.o%3Ec",
 		"types": [
 			"Person"
 		],
 		"name": "Arvind Krishna",
 		"diffbotUri": "http://diffbot.com/entity/E2w9R5RLuMCSUb511otaM-Q",
-		"targetDiffbotUri": "http://diffbot.com/entity/E2w9R5RLuMCSUb511otaM-Q",
 		"targetDiffbotId": "E2w9R5RLuMCSUb511otaM-Q",
-		"surfaceForm": "Arvind Krishna",
 		"type": "Person"
 	}
 }
 ```
+### chineseSocialCreditCodes
+  Chinese social credit code.
+* **Type:** String
+* **Example:**
+```
+{
+	"chineseSocialCreditCodes": ""
+}
+```
 ### companiesHouseIds
   Identifier assigned by the U.K. Companies House.
 * **Type:** String
@@ -299,6 +464,67 @@ Note that certain longer field examples may be truncated for readability.
 	"companiesHouseIds": ""
 }
 ```
+### competitors
+  Current competitors of this organization.
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"competitors": [
+		{
+			"summary": "American multinational technology company, a subsidiary of Alphabet Inc.",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FcvBT%3El%5D%3BTo1YMa%7B%5DX%7BGmF.yZl",
+			"types": [
+				"Organization",
+				"Corporation",
+				"Company",
+				"OrganizationInvestor"
+			],
+			"name": "Google",
+			"diffbotUri": "http://diffbot.com/entity/EUFq-3WlpNsq0pvfUYWXOEA",
+			"targetDiffbotId": "EUFq-3WlpNsq0pvfUYWXOEA",
+			"type": "Organization"
+		},
+		{
+			"summary": "American multinational technology company based in Cupertino, California",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FGvvO%3Ef%5E%3CYh%7Bf%3AHi7%5B%7B9iB.yZl",
+			"types": [
+				"Organization",
+				"Corporation",
+				"Company",
+				"OrganizationInvestor"
+			],
+			"name": "Apple Inc.",
+			"diffbotUri": "http://diffbot.com/entity/EHb0_0NEcMwyY8b083taTTw",
+			"targetDiffbotId": "EHb0_0NEcMwyY8b083taTTw",
+			"type": "Organization"
+		},
+		{
+			"summary": "American multinational technology company",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FBvqw%3Ef%5B%7Dgr%3AY7PaG.2Nm",
+			"types": [
+				"Organization",
+				"Corporation",
+				"Company",
+				"OrganizationInvestor"
+			],
+			"name": "Amazon",
+			"diffbotUri": "http://diffbot.com/entity/EU2HJUnMcNoWE3nR1cGBcZg",
+			"targetDiffbotId": "EU2HJUnMcNoWE3nR1cGBcZg",
+			"type": "Organization"
+		}
+	]
+}
+```
+### crawlTimestamp
+  The default crawlTimestamp is the most recent date of all of the crawlTimestamps of the origins used to compute the Entity, returned as a UNIX time.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"crawlTimestamp": 1757196904
+}
+```
 ### crunchbaseUri
   Link to the Crunchbase profile of this entity
 * **Type:** URL
@@ -308,16 +534,163 @@ Note that certain longer field examples may be truncated for readability.
 	"crunchbaseUri": "crunchbase.com/organization/ibm"
 }
 ```
+### cuitNumbers
+  CUIT is a unique taxpayer identifier in Argentina.
+* **Type:** String
+* **Example:**
+```
+{
+	"cuitNumbers": ""
+}
+```
+### customers
+  Current customers of this organization.
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"customers": [
+		{
+			"summary": "American multinational technology company, a subsidiary of Alphabet Inc.",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FcvBT%3El%5D%3BTo1YMa%7B%5DX%7BGmF.yZl",
+			"types": [
+				"Organization",
+				"Corporation",
+				"Company",
+				"OrganizationInvestor"
+			],
+			"name": "Google",
+			"diffbotUri": "http://diffbot.com/entity/EUFq-3WlpNsq0pvfUYWXOEA",
+			"targetDiffbotId": "EUFq-3WlpNsq0pvfUYWXOEA",
+			"type": "Organization"
+		},
+		{
+			"summary": "American multinational technology company based in Cupertino, California",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FGvvO%3Ef%5E%3CYh%7Bf%3AHi7%5B%7B9iB.yZl",
+			"types": [
+				"Organization",
+				"Corporation",
+				"Company",
+				"OrganizationInvestor"
+			],
+			"name": "Apple Inc.",
+			"diffbotUri": "http://diffbot.com/entity/EHb0_0NEcMwyY8b083taTTw",
+			"targetDiffbotId": "EHb0_0NEcMwyY8b083taTTw",
+			"type": "Organization"
+		},
+		{
+			"summary": "American multinational technology company",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FBvqw%3Ef%5B%7Dgr%3AY7PaG.2Nm",
+			"types": [
+				"Organization",
+				"Corporation",
+				"Company",
+				"OrganizationInvestor"
+			],
+			"name": "Amazon",
+			"diffbotUri": "http://diffbot.com/entity/EU2HJUnMcNoWE3nR1cGBcZg",
+			"targetDiffbotId": "EU2HJUnMcNoWE3nR1cGBcZg",
+			"type": "Organization"
+		}
+	]
+}
+```
+### description
+  A few sentences describing an entity
+* **Type:** String
+* **Example:**
+```
+{
+	"description": "International Business Machines Corp operates as an IT services and consulting company. The Company, through its platform, offers analytics, IT infrastructure, cloud, business operations and automations, cybersecurity, data storage, application development, asset management, blockchain, software, and consulting solutions. International Business Machines serves clients worldwide."
+}
+```
 ### descriptors
-  
+  A list of free-form keywords describing this entity
 * **Type:** String
 * **Example:**
 ```
 {
 	"descriptors": [
 		"computer and office equipment",
-		"data storage systems manufacturing",
-		"computer peripheral equipment manufacturing"
+		"computer hardware",
+		"business and professional services"
+	]
+}
+```
+### diffbotUri
+  diffbotUri is the URI an entity&#39;s  (URI), which is defined by appending the Diffbot ID to the URL https:&#x2F;&#x2F;diffbot.com&#x2F;entity&#x2F;. For example, Diffbot&#39;s entityID is CWSwJ_SWQPfqO3HQsxY4lGg and its DiffbotUri is https:&#x2F;&#x2F;diffbot.com&#x2F;entity&#x2F;CWSwJ_SWQPfqO3HQsxY4lGg
+* **Type:** URL
+* **Example:**
+```
+{
+	"diffbotUri": "http://diffbot.com/entity/EPdsrDmLiMQCskvBLp_dloQ"
+}
+```
+### edrpouNumbers
+  Ukrainian state registry legal entity identifier (EDRPOU).
+* **Type:** String
+* **Example:**
+```
+{
+	"edrpouNumbers": ""
+}
+```
+### emailAddresses
+  Email addresses of this organization.
+* **Type:** Contact
+* **Example:**
+```
+{
+	"emailAddresses": [
+		{
+			"contactString": "ews@us.ibm.com",
+			"type": "None"
+		},
+		{
+			"contactString": "tfleming@us.ibm.com",
+			"type": "PROFESSIONAL"
+		},
+		{
+			"contactString": "infojapan@opentable.com",
+			"type": "PROFESSIONAL"
+		}
+	]
+}
+```
+### employeeCategories
+  Employee categories including employee count and first hire date
+* **Type:** EmployeeCategory
+* **Example:**
+```
+{
+	"employeeCategories": [
+		{
+			"firstHireDate": {
+				"str": "d1945-01-XX",
+				"precision": 2,
+				"timestamp": -788918400000
+			},
+			"category": "Frontend Developer",
+			"nbEmployees": 659
+		},
+		{
+			"firstHireDate": {
+				"str": "d1959-09-XX",
+				"precision": 2,
+				"timestamp": -326160000000
+			},
+			"category": "Agriculture, Farming, Forestry and related",
+			"nbEmployees": 116
+		},
+		{
+			"firstHireDate": {
+				"str": "d1956-06-XX",
+				"precision": 2,
+				"timestamp": -428716800000
+			},
+			"category": "Industrial Production and Distribution (goods and food)",
+			"nbEmployees": 73
+		}
 	]
 }
 ```
@@ -337,6 +710,17 @@ Note that certain longer field examples may be truncated for readability.
 ```
 {
 	"founders": [
+		{
+			"summary": "American statistician and inventor（1860-1929）",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FevDp%3Em%5D8Yh%3Ec%3FI.Biv",
+			"types": [
+				"Person"
+			],
+			"name": "Herman Hollerith",
+			"diffbotUri": "http://diffbot.com/entity/EI0AIp3PNOFevRVlFf4GInw",
+			"targetDiffbotId": "EI0AIp3PNOFevRVlFf4GInw",
+			"type": "Person"
+		},
 		{
 			"summary": "American businessman",
 			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FBvqQ%3EhV%7D_o1mz3%5BFetLz63rMs%3F.%7CS%60",
@@ -345,22 +729,18 @@ Note that certain longer field examples may be truncated for readability.
 			],
 			"name": "Charles Ranlett Flint",
 			"diffbotUri": "http://diffbot.com/entity/E75wc-P6GOF2SUspkvyJygg",
-			"targetDiffbotUri": "http://diffbot.com/entity/E75wc-P6GOF2SUspkvyJygg",
 			"targetDiffbotId": "E75wc-P6GOF2SUspkvyJygg",
-			"surfaceForm": "Charles Ranlett Flint",
 			"type": "Person"
 		},
 		{
-			"summary": "American businessman; chairman and CEO of IBM",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGS%3EyV%3BZd%3FYe%40Q9m2Gt6%40x.o%3BK",
+			"summary": "American businessman and diplomat (1914-1993)",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7guSXzAoBWu.x0KwLZrUn.%5B%3CR0Aa4Hwygr9m6W%3Exl5G%60Bkxmc%3D%5D9NvfQ%7CUmGgYJ.A%5Dm",
 			"types": [
 				"Person"
 			],
-			"name": "Thomas J. Watson",
-			"diffbotUri": "http://diffbot.com/entity/Ebhc0c10rNrOp6ukkVrvrwA",
-			"targetDiffbotUri": "http://diffbot.com/entity/Ebhc0c10rNrOp6ukkVrvrwA",
-			"targetDiffbotId": "Ebhc0c10rNrOp6ukkVrvrwA",
-			"surfaceForm": "Thomas J. Watson",
+			"name": "Thomas Watson",
+			"diffbotUri": "http://diffbot.com/entity/EcIMMfNl4MtOTrv192U6q7w",
+			"targetDiffbotId": "EcIMMfNl4MtOTrv192U6q7w",
 			"type": "Person"
 		}
 	]
@@ -373,12 +753,21 @@ Note that certain longer field examples may be truncated for readability.
 ```
 {
 	"foundingDate": {
-		"str": "d1911-06-16",
+		"str": "d1911-06-01",
 		"precision": 3,
-		"timestamp": -1847577600000
+		"timestamp": -1848873600000
 	}
 }
 ```
+### fullName
+  Full name for this entity
+* **Type:** String
+* **Example:**
+```
+{
+	"fullName": "International Business Machines Corporation"
+}
+```
 ### githubUri
   Link to the Github profile of this entity
 * **Type:** URL
@@ -406,6 +795,15 @@ Note that certain longer field examples may be truncated for readability.
 	"guiNumbers": ""
 }
 ```
+### hasRemoteInternationalEmployees
+  Indicates whether the company has employees working remotely in countries without offices.
+* **Type:** Boolean
+* **Example:**
+```
+{
+	"hasRemoteInternationalEmployees": false
+}
+```
 ### homepageUri
   Link to the homepage of this  entity
 * **Type:** URL
@@ -423,39 +821,87 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"iSicClassification": [
 		{
-			"code": "",
+			"code": "2620",
 			"isPrimary": false,
-			"name": "",
-			"version": ""
+			"name": "Manufacture of computers and peripheral equipment"
+		},
+		{
+			"code": "4651",
+			"isPrimary": false,
+			"name": "Wholesale of computers, computer peripheral equipment and software"
+		},
+		{
+			"code": "6202",
+			"isPrimary": false,
+			"name": "Computer consultancy and computer facilities management activities"
 		}
 	]
 }
 ```
-### indianCorporateIdentityNumbers
-  Indian Corporate Identity Number (CIN).
+### id
+  An alphanumeric string like CWSwJ_SWQPfqO3HQsxY4lGg that uniquely identifies an entity.
 * **Type:** String
 * **Example:**
 ```
 {
-	"indianCorporateIdentityNumbers": ""
+	"id": "EPdsrDmLiMQCskvBLp_dloQ"
 }
 ```
-### industries
-  
+### image
+  The main image used to represent the entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"image": "https://kg.diffbot.com/image/api/get?fetch=yes&urls=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEo%3En0iLo%3Ba%3A.mN%60,g%3Cj7guSXzAoBWu.x0KwLZrUn.%5B%3CR0Aa4Hwygr9m6W%3Exl5G%60BkxmXg%3B%7BYr3i.Tp%3F,g%3Cj7P0Stn8p.OgAu%3CRsCX3_1BY%2F%5Dt.%5B8LwifzFeCd.Nr0QoN%5CtW4Bm5Op%7B%7CTg%7E7hraY9YU.%7C0F2"
+}
+```
+### images
+  The visual representation of an entity usually in the form of a png, jpeg, gif, or svg file.
+* **Type:** ImageField
+* **Example:**
+```
+{
+	"images": [
+		{
+			"url": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEo%3En0iLo%3Ba%3A.mN%60",
+			"primary": true
+		},
+		{
+			"url": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7guSXzAoBWu.x0KwLZrUn.%5B%3CR0Aa4Hwygr9m6W%3Exl5G%60BkxmXg%3B%7BYr3i.Tp%3F",
+			"primary": false
+		},
+		{
+			"url": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0Stn8p.OgAu%3CRsCX3_1BY%2F%5Dt.%5B8LwifzFeCd.Nr0QoN%5CtW4Bm5Op%7B%7CTg%7E7hraY9YU.%7C0F2",
+			"primary": false
+		}
+	]
+}
+```
+### importance
+  A number between 0 and 100 indicating how important or popular an entity is.
+* **Type:** Float
+* **Example:**
+```
+{
+	"importance": 98.08750915527344
+}
+```
+### indianCorporateIdentityNumbers
+  Indian Corporate Identity Number (CIN).
 * **Type:** String
 * **Example:**
 ```
 {
-	"industries": [
-		"Manufacturing Companies",
-		"Electronic Products Manufacturers",
-		"Display Technology Companies"
+	"indianCorporateIdentityNumbers": [
+		"U30007KA1991PLC012619",
+		"U72200KA1997PTC022382"
 	]
 }
 ```
 ### investments
   Investments received by this organization.
-* **Type:** Investment
+* **Type:** InvestmentField
 * **Example:**
 ```
 {
@@ -486,11 +932,8 @@ Note that certain longer field examples may be truncated for readability.
 						}
 					],
 					"types": "",
-					"websiteUris": "",
 					"diffbotUri": "",
-					"name": "",
-					"targetDiffbotUri": "",
-					"surfaceForm": ""
+					"name": ""
 				}
 			]
 		}
@@ -509,7 +952,7 @@ Note that certain longer field examples may be truncated for readability.
 			"precision": 3,
 			"timestamp": 253497600000
 		},
-		"stockExchange": "nyse"
+		"stockExchange": "New York Stock Exchange (NYSE)"
 	}
 }
 ```
@@ -561,6 +1004,15 @@ Note that certain longer field examples may be truncated for readability.
 	"isPublic": false
 }
 ```
+### israeliCompanyNumbers
+  The unique identifier given to Israeli comapnies upon registration.
+* **Type:** String
+* **Example:**
+```
+{
+	"israeliCompanyNumbers": ""
+}
+```
 ### japaneseCorporateNumbers
   The Corporate Numbers are 13-digit identifiers assigned by the National Tax Agency to companies and other organizations registered in Japan.
 * **Type:** String
@@ -570,66 +1022,39 @@ Note that certain longer field examples may be truncated for readability.
 	"japaneseCorporateNumbers": ""
 }
 ```
-### leadership
-  List of organization C-Level Officers.
-* **Type:** Employee
+### kvedClassification
+  Ukrainian Economic Activities Classification System code (KVED).
+* **Type:** ClassificationCode
 * **Example:**
 ```
 {
-	"leadership": [
+	"kvedClassification": [
 		{
-			"isCurrent": false,
-			"from": {
-				"str": "",
-				"precision": 0,
-				"timestamp": 0
-			},
-			"categories": [
-				{
-					"summary": "",
-					"image": "",
-					"images": [
-						{
-							"classifications": "",
-							"fingerprint": "",
-							"title": "",
-							"isCached": false,
-							"url": ""
-						}
-					],
-					"types": "",
-					"websiteUris": "",
-					"diffbotUri": "",
-					"name": "",
-					"targetDiffbotUri": "",
-					"surfaceForm": ""
-				}
+			"code": "",
+			"level": 0,
+			"isPrimary": false,
+			"name": "",
+			"diffbotUri": "",
+			"version": ""
+		}
+	]
+}
+```
+### legalEntities
+  Legal Entities related to this organization
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"legalEntities": [
+		{
+			"types": [
+				"LegalEntity"
 			],
-			"to": {
-				"str": "",
-				"precision": 0,
-				"timestamp": 0
-			},
-			"employee": {
-				"summary": "",
-				"image": "",
-				"images": [
-					{
-						"classifications": "",
-						"fingerprint": "",
-						"title": "",
-						"isCached": false,
-						"url": ""
-					}
-				],
-				"types": "",
-				"websiteUris": "",
-				"diffbotUri": "",
-				"name": "",
-				"targetDiffbotUri": "",
-				"surfaceForm": ""
-			},
-			"title": ""
+			"name": "IBM INDIA PRIVATE LIMITED",
+			"diffbotUri": "http://diffbot.com/entity/ETfB2TUyWNRm-C6eEfPjaLg",
+			"targetDiffbotId": "ETfB2TUyWNRm-C6eEfPjaLg",
+			"type": "LegalEntity"
 		}
 	]
 }
@@ -651,22 +1076,22 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"location": {
 		"country": {
-			"summary": "Sovereign state in North America",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEQ%3El%601Nw%7BM0Bf7hu7z%3FRe9s4XwGXedrKUAN%28%3D%5ECHnM%60%29.%7BOV",
+			"summary": "Country located primarily in North America",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ",
 			"types": [
 				"Place",
-				"AdministrativeArea"
+				"AdministrativeArea",
+				"Country"
 			],
-			"name": "United States of America",
+			"name": "United States",
 			"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
-			"targetDiffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
 			"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
-			"type": "AdministrativeArea"
+			"type": "Place"
 		},
 		"isCurrent": true,
 		"address": "1 New Orchard Road, Armonk, 10504-1722, New York, United States",
 		"city": {
-			"summary": "Hamlet in Westchester County, New York",
+			"summary": "Hamlet in Westchester County, New York, United States",
 			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FdvCo%3E%7CS%3Faf4_%3EU_JXRG%7BEa%2FCS0%5Bq%3Ch4%5Bp%40%5E1%5Ew%3Ek%3FDp%3F_p%3Bv%3DN%7DTp%3BI3Wk3dtMW4PhBc0X%5Dmo0KxFPrQp7T%2FNe%3AYy.gHZ",
 			"types": [
 				"Place",
@@ -674,10 +1099,10 @@ Note that certain longer field examples may be truncated for readability.
 			],
 			"name": "Armonk",
 			"diffbotUri": "http://diffbot.com/entity/EFYOMni-nNtScxpZwteaMxQ",
-			"targetDiffbotUri": "http://diffbot.com/entity/EFYOMni-nNtScxpZwteaMxQ",
 			"targetDiffbotId": "EFYOMni-nNtScxpZwteaMxQ",
-			"type": "AdministrativeArea"
+			"type": "Place"
 		},
+		"isPrimary": true,
 		"street": "1 New Orchard Road",
 		"latitude": 41.1134033203125,
 		"precision": 0.10000000149011612,
@@ -688,13 +1113,13 @@ Note that certain longer field examples may be truncated for readability.
 			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FevDp%3EsGo0d%3Cc%3FPfxZ%7DGx8Zg.o%3BK",
 			"types": [
 				"Place",
-				"AdministrativeArea"
+				"AdministrativeArea",
+				"Region"
 			],
 			"name": "New York",
 			"diffbotUri": "http://diffbot.com/entity/E1NxI_KXaMbiP5g2aM9MRdw",
-			"targetDiffbotUri": "http://diffbot.com/entity/E1NxI_KXaMbiP5g2aM9MRdw",
 			"targetDiffbotId": "E1NxI_KXaMbiP5g2aM9MRdw",
-			"type": "AdministrativeArea"
+			"type": "Place"
 		},
 		"longitude": -73.7203598022461
 	}
@@ -709,22 +1134,21 @@ Note that certain longer field examples may be truncated for readability.
 	"locations": [
 		{
 			"country": {
-				"summary": "Sovereign state in North America",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEQ%3El%601Nw%7BM0Bf7hu7z%3FRe9s4XwGXedrKUAN%28%3D%5ECHnM%60%29.%7BOV",
+				"summary": "Country located primarily in North America",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ",
 				"types": [
 					"Place",
-					"AdministrativeArea"
+					"AdministrativeArea",
+					"Country"
 				],
-				"name": "United States of America",
+				"name": "United States",
 				"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
-				"targetDiffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
 				"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
-				"type": "AdministrativeArea"
+				"type": "Place"
 			},
-			"isCurrent": true,
-			"address": "1 New Orchard Rd, Armonk, New York",
+			"address": "1 New Orchard Road, Armonk, 10504, New York, USA",
 			"city": {
-				"summary": "Hamlet in Westchester County, New York",
+				"summary": "Hamlet in Westchester County, New York, United States",
 				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FdvCo%3E%7CS%3Faf4_%3EU_JXRG%7BEa%2FCS0%5Bq%3Ch4%5Bp%40%5E1%5Ew%3Ek%3FDp%3F_p%3Bv%3DN%7DTp%3BI3Wk3dtMW4PhBc0X%5Dmo0KxFPrQp7T%2FNe%3AYy.gHZ",
 				"types": [
 					"Place",
@@ -732,26 +1156,11 @@ Note that certain longer field examples may be truncated for readability.
 				],
 				"name": "Armonk",
 				"diffbotUri": "http://diffbot.com/entity/EFYOMni-nNtScxpZwteaMxQ",
-				"targetDiffbotUri": "http://diffbot.com/entity/EFYOMni-nNtScxpZwteaMxQ",
 				"targetDiffbotId": "EFYOMni-nNtScxpZwteaMxQ",
-				"type": "AdministrativeArea"
-			},
-			"street": "1 New Orchard Rd",
-			"metroArea": {
-				"summary": "Most populous metropolitan area in the United States",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGp%3EsG%7B%3Ah%40l%3AQiDb39t6%7ExIf.T0J",
-				"types": [
-					"Place",
-					"AdministrativeArea"
-				],
-				"name": "New York metropolitan area",
-				"diffbotUri": "http://diffbot.com/entity/EAtK9ZhUYMKmI_UzSrYinmw",
-				"targetDiffbotUri": "http://diffbot.com/entity/EAtK9ZhUYMKmI_UzSrYinmw",
-				"targetDiffbotId": "EAtK9ZhUYMKmI_UzSrYinmw",
-				"type": "AdministrativeArea"
+				"type": "Place"
 			},
 			"subregion": {
-				"summary": "County in New York, United States. Connector between New York City/Long Island and the rest of New York",
+				"summary": "County in the State of New York, United States; Connector between New York City/Long Island and the rest of New York",
 				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FivHt%3ErO%3CLr2YiFq7R%7EJq6UoKm7MyKm%7B%5Ex6G3by1d2Vp%3FmpmwN%5D%7C_.%40%5C%7B",
 				"types": [
 					"Place",
@@ -759,120 +1168,149 @@ Note that certain longer field examples may be truncated for readability.
 				],
 				"name": "Westchester County",
 				"diffbotUri": "http://diffbot.com/entity/EoKezLIvJP82Xm_cWVQyCQA",
-				"targetDiffbotUri": "http://diffbot.com/entity/EoKezLIvJP82Xm_cWVQyCQA",
 				"targetDiffbotId": "EoKezLIvJP82Xm_cWVQyCQA",
-				"type": "AdministrativeArea"
+				"type": "Place"
 			},
-			"latitude": 41.1075439453125,
+			"latitude": 41.1134033203125,
 			"precision": 0.10000000149011612,
 			"postalCode": "10504-1722",
+			"isCurrent": true,
+			"isPrimary": true,
+			"street": "1 New Orchard Road",
+			"metroArea": {
+				"summary": "Most populous metropolitan area in the United States",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FdvCQ%3EfMBVhCY%3AGYv%5E67_F_qCH4X%3BBp%7Bdy6d6Tdci%3DLn%3FZdNiMTgx%7C6RxNi%7BQtGV%2F%40u5%5DvTpHar0%7C%3CUoGL4V%3ALouZ7Ja1gq7_sVcId%7BCxIX%7EIN6X%3CNq.%607D",
+				"types": [
+					"Place",
+					"AdministrativeArea"
+				],
+				"name": "New York metropolitan area",
+				"diffbotUri": "http://diffbot.com/entity/EAtK9ZhUYMKmI_UzSrYinmw",
+				"targetDiffbotId": "EAtK9ZhUYMKmI_UzSrYinmw",
+				"type": "Place"
+			},
 			"region": {
 				"summary": "State of the United States of America",
 				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FevDp%3EsGo0d%3Cc%3FPfxZ%7DGx8Zg.o%3BK",
 				"types": [
 					"Place",
-					"AdministrativeArea"
+					"AdministrativeArea",
+					"Region"
 				],
 				"name": "New York",
 				"diffbotUri": "http://diffbot.com/entity/E1NxI_KXaMbiP5g2aM9MRdw",
-				"targetDiffbotUri": "http://diffbot.com/entity/E1NxI_KXaMbiP5g2aM9MRdw",
 				"targetDiffbotId": "E1NxI_KXaMbiP5g2aM9MRdw",
-				"type": "AdministrativeArea"
+				"type": "Place"
 			},
-			"longitude": -73.72123718261719
+			"longitude": -73.7203598022461
 		},
 		{
 			"country": {
-				"summary": "Sovereign state in North America",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEQ%3El%601Nw%7BM0Bf7hu7z%3FRe9s4XwGXedrKUAN%28%3D%5ECHnM%60%29.%7BOV",
+				"summary": "Country located primarily in North America",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ",
 				"types": [
 					"Place",
-					"AdministrativeArea"
+					"AdministrativeArea",
+					"Country"
 				],
-				"name": "United States of America",
+				"name": "United States",
 				"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
-				"targetDiffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
 				"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
-				"type": "AdministrativeArea"
+				"type": "Place"
 			},
-			"isCurrent": false,
-			"address": "Armonk, New York",
+			"address": "6303 Barfield Rd Atlanta, GA, 30328-4233 United States",
 			"city": {
-				"summary": "Hamlet in Westchester County, New York",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FdvCo%3E%7CS%3Faf4_%3EU_JXRG%7BEa%2FCS0%5Bq%3Ch4%5Bp%40%5E1%5Ew%3Ek%3FDp%3F_p%3Bv%3DN%7DTp%3BI3Wk3dtMW4PhBc0X%5Dmo0KxFPrQp7T%2FNe%3AYy.gHZ",
+				"summary": "Capital city of Georgia, United States",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FbvAu%3EkZ%7DTb%3B%60zrnDZ%7DLg.%60%7CK",
 				"types": [
 					"Place",
-					"AdministrativeArea"
+					"AdministrativeArea",
+					"City"
 				],
-				"name": "Armonk",
-				"diffbotUri": "http://diffbot.com/entity/EFYOMni-nNtScxpZwteaMxQ",
-				"targetDiffbotUri": "http://diffbot.com/entity/EFYOMni-nNtScxpZwteaMxQ",
-				"targetDiffbotId": "EFYOMni-nNtScxpZwteaMxQ",
-				"type": "AdministrativeArea"
+				"name": "Atlanta",
+				"diffbotUri": "http://diffbot.com/entity/EP-thVRNKPCiwPfIyJ3_ozQ",
+				"targetDiffbotId": "EP-thVRNKPCiwPfIyJ3_ozQ",
+				"type": "Place"
 			},
-			"metroArea": {
-				"summary": "Most populous metropolitan area in the United States",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGp%3EsG%7B%3Ah%40l%3AQiDb39t6%7ExIf.T0J",
+			"subregion": {
+				"summary": "County in Georgia, United States",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FbvAr%3ErO%3CLr2YbFiJ%60x9e%3FVmLq4KzWb0Wpme%3Act%3C%5B%60RqHo%3A.%7BOV",
 				"types": [
 					"Place",
-					"AdministrativeArea"
+					"AdministrativeArea",
+					"Subregion"
 				],
-				"name": "New York metropolitan area",
-				"diffbotUri": "http://diffbot.com/entity/EAtK9ZhUYMKmI_UzSrYinmw",
-				"targetDiffbotUri": "http://diffbot.com/entity/EAtK9ZhUYMKmI_UzSrYinmw",
-				"targetDiffbotId": "EAtK9ZhUYMKmI_UzSrYinmw",
-				"type": "AdministrativeArea"
+				"name": "Fulton County",
+				"diffbotUri": "http://diffbot.com/entity/Eav8t1QygMqC_KrJ9RJdcKw",
+				"targetDiffbotId": "Eav8t1QygMqC_KrJ9RJdcKw",
+				"type": "Place"
 			},
-			"subregion": {
-				"summary": "County in New York, United States. Connector between New York City/Long Island and the rest of New York",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FivHt%3ErO%3CLr2YiFq7R%7EJq6UoKm7MyKm%7B%5Ex6G3by1d2Vp%3FmpmwN%5D%7C_.%40%5C%7B",
+			"latitude": 33.769805908203125,
+			"precision": 18.72922134399414,
+			"postalCode": "30328-4233",
+			"isCurrent": true,
+			"isPrimary": false,
+			"street": "6303 Barfield Rd",
+			"metroArea": {
+				"summary": "Most populous metro area in the US state of Georgia",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FFvuw%3Egc%2FXk1%5B%2F%40gA%5D3G%7DELjS%7C9X1ZgqQ5CQ%3Ccf.f%3DJ",
 				"types": [
 					"Place",
 					"AdministrativeArea"
 				],
-				"name": "Westchester County",
-				"diffbotUri": "http://diffbot.com/entity/EoKezLIvJP82Xm_cWVQyCQA",
-				"targetDiffbotUri": "http://diffbot.com/entity/EoKezLIvJP82Xm_cWVQyCQA",
-				"targetDiffbotId": "EoKezLIvJP82Xm_cWVQyCQA",
-				"type": "AdministrativeArea"
+				"name": "Atlanta-Sandy Springs-Roswell metropolitan area",
+				"diffbotUri": "http://diffbot.com/entity/ERy8LbfAgONKM1PFREToBJw",
+				"targetDiffbotId": "ERy8LbfAgONKM1PFREToBJw",
+				"type": "Place"
 			},
-			"latitude": 41.131256103515625,
-			"precision": 3.956873655319214,
-			"postalCode": "10504",
 			"region": {
 				"summary": "State of the United States of America",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FevDp%3EsGo0d%3Cc%3FPfxZ%7DGx8Zg.o%3BK",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3Fav%40v%3EkZ%7DTb%3B%60zUb%3DXbLgKReSkz%7BwRkyYr.cDV",
 				"types": [
 					"Place",
-					"AdministrativeArea"
+					"AdministrativeArea",
+					"Region"
 				],
-				"name": "New York",
-				"diffbotUri": "http://diffbot.com/entity/E1NxI_KXaMbiP5g2aM9MRdw",
-				"targetDiffbotUri": "http://diffbot.com/entity/E1NxI_KXaMbiP5g2aM9MRdw",
-				"targetDiffbotId": "E1NxI_KXaMbiP5g2aM9MRdw",
-				"type": "AdministrativeArea"
+				"name": "Georgia",
+				"diffbotUri": "http://diffbot.com/entity/E_L-1Z6pbMUuEvXV5RpTMaQ",
+				"targetDiffbotId": "E_L-1Z6pbMUuEvXV5RpTMaQ",
+				"type": "Place"
 			},
-			"longitude": -73.71214294433594
+			"longitude": -84.41458129882812
 		},
 		{
 			"country": {
-				"summary": "Sovereign state in North America",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEQ%3El%601Nw%7BM0Bf7hu7z%3FRe9s4XwGXedrKUAN%28%3D%5ECHnM%60%29.%7BOV",
+				"summary": "Country in north-west Europe",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FBvqs%3EkZ%7DTb%3B%60zUb%3DXdFoKRjCP4RyGh%2FO%28X-P%29.Ar4",
+				"types": [
+					"Place",
+					"AdministrativeArea",
+					"Country"
+				],
+				"name": "United Kingdom",
+				"diffbotUri": "http://diffbot.com/entity/EnI6g1AI9NcC6yCohEYEb2A",
+				"targetDiffbotId": "EnI6g1AI9NcC6yCohEYEb2A",
+				"type": "Place"
+			},
+			"address": "8 Weybridge Business Park Unit, Weybridge, Surrey, United Kingdom",
+			"isPrimary": false,
+			"street": "8 Weybridge Business Park Unit",
+			"latitude": 51.25234603881836,
+			"precision": 40.80295944213867,
+			"postalCode": "KT15 2UF",
+			"region": {
+				"summary": "County of England",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FgvFu%3Exc%3E_hEYp%7CYDhr9zF_eQf%3BCDczB.4MW",
 				"types": [
 					"Place",
 					"AdministrativeArea"
 				],
-				"name": "United States of America",
-				"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
-				"targetDiffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
-				"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
-				"type": "AdministrativeArea"
+				"name": "Surrey",
+				"diffbotUri": "http://diffbot.com/entity/EtjOVkZlUNryQgUt_ftmKgw",
+				"targetDiffbotId": "EtjOVkZlUNryQgUt_ftmKgw",
+				"type": "Place"
 			},
-			"isCurrent": false,
-			"address": "United States",
-			"latitude": 39.71595764160156,
-			"precision": 3133.158935546875,
-			"longitude": -96.99966430664062
+			"longitude": -0.47444701194763184
 		}
 	]
 }
@@ -895,8 +1333,10 @@ Note that certain longer field examples may be truncated for readability.
 	"mccClassification": [
 		{
 			"code": "",
+			"level": 0,
 			"isPrimary": false,
 			"name": "",
+			"diffbotUri": "",
 			"version": ""
 		}
 	]
@@ -920,29 +1360,132 @@ Note that certain longer field examples may be truncated for readability.
 	"mccCodeDescription": ""
 }
 ```
+### monthlyTraffic
+  Monthly website traffic on this organization&#39;s homepage
+* **Type:** Integer
+* **Example:**
+```
+{
+	"monthlyTraffic": 113412519
+}
+```
+### monthlyTrafficGrowth
+  Monthly growth in website traffic on this organization&#39;s homepage
+* **Type:** Float
+* **Example:**
+```
+{
+	"monthlyTrafficGrowth": -0.31240857
+}
+```
 ### motto
   A short sentence or phrase chosen as encapsulating the beliefs or ideals guiding an organization
 * **Type:** String
 * **Example:**
 ```
 {
-	"motto": "We're using technologies like AI, cloud, blockchain and IoT to help our clients transform their industries."
+	"motto": "Market Research analyst- GfK"
 }
 ```
 ### naceClassification
-  The Statistical classification of economic activities in the European Community (NACE) is is a 4-digit classification providing the framework for collecting and presenting a large range of statistical data. We use NACE Rev. 2 (2008).
-* **Type:** ClassificationCode
-* **Example:**
+
+The `naceClassification` field encodes the NACE Rev. 2.1 classification of economic activities associated with an entity.
+
+The NACE classification of economic activities in the European Community is used for a wide variety of European statistics in the economic, social, environmental, and agricultural domains.
+
+Each entry follows the hierarchical NACE structure:
+
+ Sections (letters A–V, level 1)  
+ Divisions (2 digits, level 2)  
+ Groups (3 digits with dot, level 3)  
+ Classes (4 digits with dot, level 4)
+
+This field may contain multiple codes. At most one code per level can be marked as isPrimary: true.
+
+- **Type:** ClassificationCode
+- **Example:**
+
 ```
 {
 	"naceClassification": [
-		{
-			"code": "",
-			"isPrimary": false,
-			"name": "",
-			"version": ""
-		}
-	]
+    {
+        "code": "58.29",
+        "level": 4,
+        "isPrimary": true,
+        "name": "Other software publishing",
+        "version": "Rev 2.1"
+    },
+    {
+        "code": "58.2",
+        "level": 3,
+        "isPrimary": true,
+        "name": "Software publishing",
+        "version": "Rev 2.1"
+    },
+    {
+        "code": "58",
+        "level": 2,
+        "isPrimary": true,
+        "name": "Publishing activities",
+        "version": "Rev 2.1"
+    },
+    {
+        "code": "J",
+        "level": 1,
+        "isPrimary": true,
+        "name": "PUBLISHING, BROADCASTING, AND CONTENT PRODUCTION AND DISTRIBUTION ACTIVITIES",
+        "version": "Rev 2.1"
+    },
+    {
+        "code": "26.20",
+        "level": 4,
+        "isPrimary": false,
+        "name": "Manufacture of computers and peripheral equipment",
+        "version": "Rev 2.1"
+    },
+    {
+        "code": "26.2",
+        "level": 3,
+        "isPrimary": false,
+        "name": "Manufacture of computers and peripheral equipment",
+        "version": "Rev 2.1"
+    },
+    {
+        "code": "26",
+        "level": 2,
+        "isPrimary": false,
+        "name": "Manufacture of computer, electronic and optical products",
+        "version": "Rev 2.1"
+    },
+    {
+        "code": "C",
+        "level": 1,
+        "isPrimary": false,
+        "name": "MANUFACTURING",
+        "version": "Rev 2.1"
+    },
+    {
+        "code": "62.9",
+        "level": 3,
+        "isPrimary": false,
+        "name": "Other information technology and computer service activities",
+        "version": "Rev 2.1"
+    },
+    {
+        "code": "62",
+        "level": 2,
+        "isPrimary": false,
+        "name": "Computer programming, consultancy and related activities",
+        "version": "Rev 2.1"
+    },
+    {
+        "code": "K",
+        "level": 1,
+        "isPrimary": false,
+        "name": "TELECOMMUNICATION, COMPUTER PROGRAMMING, CONSULTING, COMPUTING INFRASTRUCTURE AND OTHER INFORMATION SERVICE ACTIVITIES",
+        "version": "Rev 2.1"
+    }
+]
 }
 ```
 ### nafClassification
@@ -953,46 +1496,85 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"nafClassification": [
 		{
-			"code": "",
+			"code": "70.22z",
 			"isPrimary": false,
-			"name": "",
-			"version": ""
+			"name": "Business and other management consultancy activities"
 		}
 	]
 }
 ```
 ### naicsClassification
-  The North American Industry Classification System (NAICS) is the standard used by Federal statistical agencies in classifying business establishments for the purpose of collecting, analyzing, and publishing statistical data related to the U.S. business economy.
+  The North American Industry Classification System (NAICS) is the standard used by Federal statistical agencies in classifying business establishments for the purpose of collecting, analyzing, and publishing statistical data related to the U.S. business economy. This is the 2022 version.
 * **Type:** ClassificationCode
 * **Example:**
 ```
 {
 	"naicsClassification": [
 		{
-			"code": "522220",
-			"isPrimary": false,
-			"name": "Sales Financing"
+			"code": "334110",
+			"level": 4,
+			"isPrimary": true,
+			"name": "Computer and Peripheral Equipment Manufacturing"
 		},
 		{
-			"code": "330000",
-			"isPrimary": false,
-			"name": "Manufacturing"
+			"code": "334100",
+			"level": 3,
+			"isPrimary": true,
+			"name": "Computer and Peripheral Equipment Manufacturing"
 		},
 		{
-			"code": "335000",
-			"isPrimary": false,
-			"name": "Electrical Equipment, Appliance, and Component Manufacturing"
+			"code": "334000",
+			"level": 2,
+			"isPrimary": true,
+			"name": "Computer and Electronic Product Manufacturing"
 		}
 	]
 }
 ```
+### naicsClassification2017
+  The North American Industry Classification System (NAICS) is the standard used by Federal statistical agencies in classifying business establishments for the purpose of collecting, analyzing, and publishing statistical data related to the U.S. business economy. This is the 2017 version.
+* **Type:** ClassificationCode
+* **Example:**
+```
+{
+	"naicsClassification2017": [
+		{
+			"code": "334110",
+			"level": 4,
+			"isPrimary": true,
+			"name": "Computer and Peripheral Equipment Manufacturing"
+		},
+		{
+			"code": "334100",
+			"level": 3,
+			"isPrimary": true,
+			"name": "Computer and Peripheral Equipment Manufacturing"
+		},
+		{
+			"code": "334000",
+			"level": 2,
+			"isPrimary": true,
+			"name": "Computer and Electronic Product Manufacturing"
+		}
+	]
+}
+```
+### name
+  Primary text label for this entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"name": "IBM"
+}
+```
 ### nbActiveEmployeeEdges
   Number of employees in the Diffbot KG who are currently employed by this organization.
 * **Type:** Integer
 * **Example:**
 ```
 {
-	"nbActiveEmployeeEdges": 162466
+	"nbActiveEmployeeEdges": 117969
 }
 ```
 ### nbEmployeeRanges
@@ -1015,7 +1597,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"nbEmployees": 345000
+	"nbEmployees": 300000
 }
 ```
 ### nbEmployeesMax
@@ -1024,7 +1606,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"nbEmployeesMax": 345000
+	"nbEmployeesMax": 300000
 }
 ```
 ### nbEmployeesMin
@@ -1033,43 +1615,34 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"nbEmployeesMin": 345000
+	"nbEmployeesMin": 300000
 }
 ```
-### nbEmployeesOnLinkedIn
-  Number of employees with LinkedIn profiles as reported by LinkedIn.
+### nbIncomingEdges
+  This is the number of edges in the Knowledge Graph that point to this entity. For example, the nbIncomingEdges field for Google is over 100,000. This number includes the number of people that work at google, the number of investors who invested in google, etc.
 * **Type:** Integer
 * **Example:**
 ```
 {
-	"nbEmployeesOnLinkedIn": 0
+	"nbIncomingEdges": 2040792
 }
 ```
-### nbEmployeesOnLinkedInOverTime
-  Number of employees with LinkedIn profiles as reported by LinkedIn over time. This includes the latest number reported by LinkedIn.
-* **Type:** ObservationInt
+### nbLocations
+  Number of locations listed in the field &#39;locations&#39;
+* **Type:** Integer
 * **Example:**
 ```
 {
-	"nbEmployeesOnLinkedInOverTime": [
-		{
-			"observationDate": {
-				"str": "",
-				"precision": 0,
-				"timestamp": 0
-			},
-			"observationValue": 0
-		}
-	]
+	"nbLocations": 694
 }
 ```
-### nbLocations
-  Number of locations listed in the field &#39;locations&#39;
+### nbOrigins
+  Total number of origins in the field &#39;origins&#39;. This field is only available in extended JSON mode.
 * **Type:** Integer
 * **Example:**
 ```
 {
-	"nbLocations": 47
+	"nbOrigins": 6912
 }
 ```
 ### nbUniqueInvestors
@@ -1081,6 +1654,15 @@ Note that certain longer field examples may be truncated for readability.
 	"nbUniqueInvestors": 0
 }
 ```
+### nonCanonicalFacts
+  Enumerates all the non-canonical fields (i.e., those not defined in the ontology) that have a value for this entity. For instance, if &#39;numberOfChildren&#39; is listed in &#39;nonCanonicalFacts&#39; then the entity JSON will have the key &#39;numberOfChildren&#39; with an associated value. This field is only provided when the parameter nonCanonicalFacts&#x3D;1 is set. See: https:&#x2F;&#x2F;docs.diffbot.com&#x2F;kgapi
+* **Type:** String
+* **Example:**
+```
+{
+	"nonCanonicalFacts": ""
+}
+```
 ### norwegianOrganizationNumbers
   Organisation&#39;s identifier in the Norwegian Central Coordinating Register for Legal Entities.
 * **Type:** String
@@ -1090,6 +1672,15 @@ Note that certain longer field examples may be truncated for readability.
 	"norwegianOrganizationNumbers": ""
 }
 ```
+### npiNumbers
+  The National Provider Identifier (NPI) is a unique identification number for covered health care providers. 
+* **Type:** String
+* **Example:**
+```
+{
+	"npiNumbers": ""
+}
+```
 ### okvedClassification
   Russian Economic Activities Classification System code (OKVED).
 * **Type:** ClassificationCode
@@ -1099,13 +1690,46 @@ Note that certain longer field examples may be truncated for readability.
 	"okvedClassification": [
 		{
 			"code": "",
+			"level": 0,
 			"isPrimary": false,
 			"name": "",
+			"diffbotUri": "",
 			"version": ""
 		}
 	]
 }
 ```
+### originDetails
+  Additional information about origins listed in &#39;origins&#39;, including the latest time it was crawled. This field is only available in extended JSON mode.
+* **Type:** OriginDetail
+* **Example:**
+```
+{
+	"originDetails": [
+		{
+			"crawledAt": {
+				"str": "",
+				"precision": 0,
+				"timestamp": 0
+			},
+			"origin": ""
+		}
+	]
+}
+```
+### origins
+  An origin is a web address where Diffbot found one or more facts about an entity. This field is only available in extended JSON mode.
+* **Type:** String
+* **Example:**
+```
+{
+	"origins": [
+		"01net.it/sirion-ranks-highest-in-all-four-use-cases-in-2024-gartner-critical-capabilities-for-contract-life-cycle-management",
+		"101blockchains.com",
+		"10bestpr.com/pr-agencies/sf/2016/september/launchsquad"
+	]
+}
+```
 ### parentCompany
   The parent company of this subsidiary.
 * **Type:** LinkedEntity
@@ -1125,14 +1749,63 @@ Note that certain longer field examples may be truncated for readability.
 			}
 		],
 		"types": "",
-		"websiteUris": "",
 		"diffbotUri": "",
-		"name": "",
-		"targetDiffbotUri": "",
-		"surfaceForm": ""
+		"name": ""
 	}
 }
 ```
+### partnerships
+  Current partnerships of this organization.
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"partnerships": [
+		{
+			"summary": "American multinational technology company, a subsidiary of Alphabet Inc.",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FcvBT%3El%5D%3BTo1YMa%7B%5DX%7BGmF.yZl",
+			"types": [
+				"Organization",
+				"Corporation",
+				"Company",
+				"OrganizationInvestor"
+			],
+			"name": "Google",
+			"diffbotUri": "http://diffbot.com/entity/EUFq-3WlpNsq0pvfUYWXOEA",
+			"targetDiffbotId": "EUFq-3WlpNsq0pvfUYWXOEA",
+			"type": "Organization"
+		},
+		{
+			"summary": "American multinational technology corporation",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FjvIt%3ErW%2F_r%3Fi1UYDhvGe%25o%3Ef5Lf%25e2.c7%3E",
+			"types": [
+				"Organization",
+				"Corporation",
+				"Company",
+				"OrganizationInvestor"
+			],
+			"name": "Microsoft",
+			"diffbotUri": "http://diffbot.com/entity/EIsFKrN_ZNLSWsvxdQfWutQ",
+			"targetDiffbotId": "EIsFKrN_ZNLSWsvxdQfWutQ",
+			"type": "Organization"
+		},
+		{
+			"summary": "South Korean multinational conglomerate",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0SttAc%3ANu.d9U%7CB%5DpM08.%7DZnIa6%40_%3Bv2FpDLhawxEr-%5BuTpJZ%40-r%3Ec2Jh9e%3ENt%3B_%7DPwTLtS%5Cut%7DJUOtz",
+			"types": [
+				"Organization",
+				"Corporation",
+				"Company",
+				"OrganizationInvestor"
+			],
+			"name": "Samsung Electronics",
+			"diffbotUri": "http://diffbot.com/entity/EEUocPTqVNCGf3f-wqw6lxQ",
+			"targetDiffbotId": "EEUocPTqVNCGf3f-wqw6lxQ",
+			"type": "Organization"
+		}
+	]
+}
+```
 ### phoneNumbers
   Phone numbers of this organization.
 * **Type:** PhoneNumber
@@ -1159,29 +1832,35 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"predecessors": [
 		{
-			"summary": "",
-			"image": "",
-			"images": [
-				{
-					"classifications": "",
-					"fingerprint": "",
-					"title": "",
-					"isCached": false,
-					"url": ""
-				}
+			"summary": "American business machines company",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FBvqs%3EhBnLF%3Bg%3BBhQX%5BGmF.vRl",
+			"types": [
+				"Organization",
+				"Corporation",
+				"Company"
 			],
-			"types": "",
-			"websiteUris": "",
-			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
+			"name": "Computing Tabulating Recording Company",
+			"diffbotUri": "http://diffbot.com/entity/EeCTt6xVqOoqWn5jzd4EwCw",
+			"targetDiffbotId": "EeCTt6xVqOoqWn5jzd4EwCw",
+			"type": "Organization"
+		},
+		{
+			"summary": "American manufacturing company",
+			"types": [
+				"Organization",
+				"Corporation",
+				"Company"
+			],
+			"name": "Bundy Manufacturing Company",
+			"diffbotUri": "http://diffbot.com/entity/Ex0oc7IVgNWGUSnSDoTUV-w",
+			"targetDiffbotId": "Ex0oc7IVgNWGUSnSDoTUV-w",
+			"type": "Organization"
 		}
 	]
 }
 ```
 ### quarterlyRevenues
-  An organization&#39;s revenue for a period of 3 months.
+  An organization&#39;s officially reported revenue for a period of 3 months.
 * **Type:** QuarterlyRevenue
 * **Example:**
 ```
@@ -1190,72 +1869,81 @@ Note that certain longer field examples may be truncated for readability.
 		{
 			"revenue": {
 				"currency": "USD",
-				"value": 24673000000
+				"value": 14541000000
 			},
 			"isCurrent": false,
-			"year": 2012,
+			"year": 2025,
 			"filingDate": {
-				"str": "d2013-03-31",
+				"str": "d2025-04-24",
 				"precision": 3,
-				"timestamp": 1364688000000
+				"timestamp": 1745452800000
 			},
 			"revenueDate": {
-				"str": "d2012-03-31",
+				"str": "d2025-03-31",
 				"precision": 3,
-				"timestamp": 1333152000000
+				"timestamp": 1743379200000
 			},
 			"quarter": 1
 		},
 		{
 			"revenue": {
 				"currency": "USD",
-				"value": 26666000000
+				"value": 14968000000
 			},
 			"isCurrent": false,
-			"year": 2011,
+			"year": 2024,
 			"filingDate": {
-				"str": "d2012-06-30",
+				"str": "d2024-10-30",
 				"precision": 3,
-				"timestamp": 1341014400000
+				"timestamp": 1730246400000
 			},
 			"revenueDate": {
-				"str": "d2011-06-30",
+				"str": "d2024-09-30",
 				"precision": 3,
-				"timestamp": 1309392000000
+				"timestamp": 1727654400000
 			},
-			"quarter": 2
+			"quarter": 3
 		},
 		{
 			"revenue": {
 				"currency": "USD",
-				"value": 26157000000
+				"value": 15770000000
 			},
 			"isCurrent": false,
-			"year": 2011,
+			"year": 2024,
 			"filingDate": {
-				"str": "d2012-09-30",
+				"str": "d2024-07-30",
 				"precision": 3,
-				"timestamp": 1348963200000
+				"timestamp": 1722297600000
 			},
 			"revenueDate": {
-				"str": "d2011-09-30",
+				"str": "d2024-06-30",
 				"precision": 3,
-				"timestamp": 1317340800000
+				"timestamp": 1719705600000
 			},
-			"quarter": 3
+			"quarter": 2
 		}
 	]
 }
 ```
+### remoteScore
+  The probability (0-1) of work environment for this organization to be remote&#x2F;hybrid and not in_person, i.e. higher the value of remoteScore, the more likely the organization has remote&#x2F;hybrid work environment.
+* **Type:** Float
+* **Example:**
+```
+{
+	"remoteScore": 0.8075339
+}
+```
 ### revenue
-  Income, especially that of a company or organization, generated from the sales of goods, services, capital or any other assets.
+  Most recent yearly revenue as reported by the organization or estimated using a model. If the revenue amount is estimated, revenue.explicitOrigin is set to &#39;inference&#39;. See also: yearlyRevenues.
 * **Type:** Amount
 * **Example:**
 ```
 {
 	"revenue": {
 		"currency": "USD",
-		"value": 73620000000
+		"value": 62753000000
 	}
 }
 ```
@@ -1275,66 +1963,59 @@ Note that certain longer field examples may be truncated for readability.
 ```
 {
 	"secCentralIndexKeys": [
-		"0000051143",
 		"51143"
 	]
 }
 ```
 ### secForms
-  Financial statements or other documents filed by this organizations to the U.S. Securities and Exchange Commission (SEC).
+  Financial statements or other documents filed by this organizations with the U.S. Securities and Exchange Commission (SEC) from 1994 to present.
 * **Type:** SECForm
 * **Example:**
 ```
 {
 	"secForms": [
 		{
-			"formType": "8-K/A",
-			"periodOfReport": {
-				"str": "d2019-06-30",
-				"precision": 3,
-				"timestamp": 1561852800000
-			},
+			"formType": "8-K",
 			"filingDate": {
-				"str": "d2019-09-20",
+				"str": "d2025-07-23",
 				"precision": 3,
-				"timestamp": 1568937600000
+				"timestamp": 1753228800000
 			},
-			"documentUrl": "https://www.sec.gov/ix?doc=/Archives/edgar/data/51143/000155837019008675/ibm-20190709x8ka.htm",
-			"filingUrl": "https://www.sec.gov/Archives/edgar/data/51143/000155837019008675/0001558370-19-008675-index.htm"
+			"documentUrl": "https://www.sec.gov/Archives/edgar/data/51143/000005114325000048/ibm-20250723.htm",
+			"filingUrl": "https://www.sec.gov/Archives/edgar/data/51143/000005114325000048/0000051143-25-000048-index.htm"
 		},
 		{
-			"formType": "10-Q",
-			"periodOfReport": {
-				"str": "d2019-06-30",
-				"precision": 3,
-				"timestamp": 1561852800000
-			},
+			"formType": "8-K",
 			"filingDate": {
-				"str": "d2019-07-30",
+				"str": "d2025-06-20",
 				"precision": 3,
-				"timestamp": 1564444800000
+				"timestamp": 1750377600000
 			},
-			"documentUrl": "https://www.sec.gov/ix?doc=/Archives/edgar/data/51143/000155837019006560/ibm-20190630x10q.htm",
-			"filingUrl": "https://www.sec.gov/Archives/edgar/data/51143/000155837019006560/0001558370-19-006560-index.htm"
+			"documentUrl": "https://www.sec.gov/Archives/edgar/data/51143/000095015725000533/form8-k.htm",
+			"filingUrl": "https://www.sec.gov/Archives/edgar/data/51143/000095015725000533/0000950157-25-000533-index.htm"
 		},
 		{
 			"formType": "8-K",
-			"periodOfReport": {
-				"str": "d2019-07-31",
-				"precision": 3,
-				"timestamp": 1564531200000
-			},
 			"filingDate": {
-				"str": "d2019-08-02",
+				"str": "d2025-05-02",
 				"precision": 3,
-				"timestamp": 1564704000000
+				"timestamp": 1746144000000
 			},
-			"documentUrl": "https://www.sec.gov/ix?doc=/Archives/edgar/data/51143/000155837019006914/ibm-20190802x8k.htm",
-			"filingUrl": "https://www.sec.gov/Archives/edgar/data/51143/000155837019006914/0001558370-19-006914-index.htm"
+			"documentUrl": "https://www.sec.gov/Archives/edgar/data/51143/000110465925044116/tm2513847d1_8k.htm",
+			"filingUrl": "https://www.sec.gov/Archives/edgar/data/51143/000110465925044116/0001104659-25-044116-index.htm"
 		}
 	]
 }
 ```
+### sepaIds
+  Single Euro Payments Area (SEPA) Identifier is given to European organizations located in Euro zone.
+* **Type:** String
+* **Example:**
+```
+{
+	"sepaIds": ""
+}
+```
 ### sicClassification
   The Standard Industrial Classification (SIC) is a system for classifying industries by a four-digit code. We use the version adopted by the U.S. Securities and Exchange Commission.
 * **Type:** ClassificationCode
@@ -1343,19 +2024,22 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"sicClassification": [
 		{
-			"code": "3570",
-			"isPrimary": false,
-			"name": "Computer And Office Equipment"
+			"code": "5734",
+			"level": 3,
+			"isPrimary": true,
+			"name": "Computer And Computer Software Stores"
 		},
 		{
-			"code": "4000",
-			"isPrimary": false,
-			"name": "Railroad Transportation"
+			"code": "5730",
+			"level": 2,
+			"isPrimary": true,
+			"name": "Radio, Television, Consumer Electronics, And Music Stores"
 		},
 		{
-			"code": "3500",
-			"isPrimary": false,
-			"name": "Industrial machinery and equipment"
+			"code": "5700",
+			"level": 1,
+			"isPrimary": true,
+			"name": "Home Furniture, Furnishings, And Equipment Stores"
 		}
 	]
 }
@@ -1384,7 +2068,9 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"sirenCodes": ""
+	"sirenCodes": [
+		"890677800"
+	]
 }
 ```
 ### ssbClassification
@@ -1396,8 +2082,10 @@ Note that certain longer field examples may be truncated for readability.
 	"ssbClassification": [
 		{
 			"code": "",
+			"level": 0,
 			"isPrimary": false,
 			"name": "",
+			"diffbotUri": "",
 			"version": ""
 		}
 	]
@@ -1411,7 +2099,13 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"stock": {
 		"symbol": "IBM",
-		"exchange": "NYSE"
+		"isCurrent": true,
+		"exchange": "New York Stock Exchange (NYSE)",
+		"from": {
+			"str": "d1962-01-02",
+			"precision": 3,
+			"timestamp": -252374400000
+		}
 	}
 }
 ```
@@ -1423,45 +2117,45 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"subsidiaries": [
 		{
-			"summary": "Business enterprise",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St%7D9u.LnOv%7BI%7C%40g7.pBYINs%3Ff%7CGZ7jr-tGZhWf%3DK%2FOvy%5Bp%3CSKbs8i%7CEyNzBa%3DXu9h%3DKcsg%5CFUA%5Dx3S%3A%2F%7C3h1%601Ba%40%3CTnki1nHH%5EI.3GY",
+			"summary": "American multinational software company",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0Stn8p.OgAu%3CRsCX3_1BY%2F%5Dt.%5B8LwifzFeCd.Nr0QoN%5CtW4Bm%3ERg-b%7CUY%5E%7DF.%7D%3COv",
 			"types": [
 				"Organization",
-				"Corporation"
+				"Corporation",
+				"Company",
+				"OrganizationInvestor"
 			],
-			"name": "SoftLayer Technologies, Inc.",
-			"diffbotUri": "http://diffbot.com/entity/Eo3z6VKzPNxmoKVCMdwfvmw",
-			"targetDiffbotUri": "http://diffbot.com/entity/Eo3z6VKzPNxmoKVCMdwfvmw",
-			"targetDiffbotId": "Eo3z6VKzPNxmoKVCMdwfvmw",
-			"surfaceForm": "SoftLayer Technologies, Inc.",
-			"type": "Corporation"
+			"name": "Red Hat",
+			"diffbotUri": "http://diffbot.com/entity/EIATbb7uwOhSYiGqLBPUD0w",
+			"targetDiffbotId": "EIATbb7uwOhSYiGqLBPUD0w",
+			"type": "Organization"
 		},
 		{
-			"summary": "American multinational software company",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv73%3AY3i2Pk%3F3%5CtMW6b%7B9r3izczY2.K%7C%3E",
+			"summary": "Software company",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FivHn%3EmO%3FUl_i%3DQYthvGeE%5CeXjCX.Sgy",
 			"types": [
 				"Organization",
-				"Corporation"
+				"Corporation",
+				"Company"
 			],
-			"name": "Red Hat, Inc.",
-			"diffbotUri": "http://diffbot.com/entity/EIATbb7uwOhSYiGqLBPUD0w",
-			"targetDiffbotUri": "http://diffbot.com/entity/EIATbb7uwOhSYiGqLBPUD0w",
-			"targetDiffbotId": "EIATbb7uwOhSYiGqLBPUD0w",
-			"surfaceForm": "Red Hat, Inc.",
-			"type": "Corporation"
+			"name": "HashiCorp",
+			"diffbotUri": "http://diffbot.com/entity/E9N3XMWjUM_2dU66HUna5GQ",
+			"targetDiffbotId": "E9N3XMWjUM_2dU66HUna5GQ",
+			"type": "Organization"
 		},
 		{
-			"summary": "Corporation based in Egypt",
+			"summary": "Software as a service company",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0Stn8p.%5DjEp9G.Bd%7Bko6u%7CoeR%5B-f%5B9z-Z%3BVP-C%3CMG-c%7BGwuYPRmeM%2FzN_%3Cb4E.A%5Dm",
 			"types": [
 				"Organization",
-				"Corporation"
+				"Corporation",
+				"Company",
+				"OrganizationInvestor"
 			],
-			"name": "IBM Egypt Business Support Services",
-			"diffbotUri": "http://diffbot.com/entity/EqxFQye0mN_mBtveIsJwWmg",
-			"targetDiffbotUri": "http://diffbot.com/entity/EqxFQye0mN_mBtveIsJwWmg",
-			"targetDiffbotId": "EqxFQye0mN_mBtveIsJwWmg",
-			"surfaceForm": "IBM Egypt Business Support Services",
-			"type": "Corporation"
+			"name": "Diligent",
+			"diffbotUri": "http://diffbot.com/entity/EWOVULEdSNbunhBcIF6MtKQ",
+			"targetDiffbotId": "EWOVULEdSNbunhBcIF6MtKQ",
+			"type": "Organization"
 		}
 	]
 }
@@ -1486,17 +2180,75 @@ Note that certain longer field examples may be truncated for readability.
 				}
 			],
 			"types": "",
-			"websiteUris": "",
 			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
+			"name": ""
+		}
+	]
+}
+```
+### summary
+  A short phrase designed to disambiguate entities with the same or similar name
+* **Type:** String
+* **Example:**
+```
+{
+	"summary": "American multinational technology corporation"
+}
+```
+### suppliers
+  Current suppliers of this organization.
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"suppliers": [
+		{
+			"summary": "American multinational technology company, a subsidiary of Alphabet Inc.",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FcvBT%3El%5D%3BTo1YMa%7B%5DX%7BGmF.yZl",
+			"types": [
+				"Organization",
+				"Corporation",
+				"Company",
+				"OrganizationInvestor"
+			],
+			"name": "Google",
+			"diffbotUri": "http://diffbot.com/entity/EUFq-3WlpNsq0pvfUYWXOEA",
+			"targetDiffbotId": "EUFq-3WlpNsq0pvfUYWXOEA",
+			"type": "Organization"
+		},
+		{
+			"summary": "American multinational technology corporation",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FjvIt%3ErW%2F_r%3Fi1UYDhvGe%25o%3Ef5Lf%25e2.c7%3E",
+			"types": [
+				"Organization",
+				"Corporation",
+				"Company",
+				"OrganizationInvestor"
+			],
+			"name": "Microsoft",
+			"diffbotUri": "http://diffbot.com/entity/EIsFKrN_ZNLSWsvxdQfWutQ",
+			"targetDiffbotId": "EIsFKrN_ZNLSWsvxdQfWutQ",
+			"type": "Organization"
+		},
+		{
+			"summary": "South Korean multinational conglomerate",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0SttAc%3ANu.d9U%7CB%5DpM08.%7DZnIa6%40_%3Bv2FpDLhawxEr-%5BuTpJZ%40-r%3Ec2Jh9e%3ENt%3B_%7DPwTLtS%5Cut%7DJUOtz",
+			"types": [
+				"Organization",
+				"Corporation",
+				"Company",
+				"OrganizationInvestor"
+			],
+			"name": "Samsung Electronics",
+			"diffbotUri": "http://diffbot.com/entity/EEUocPTqVNCGf3f-wqw6lxQ",
+			"targetDiffbotId": "EEUocPTqVNCGf3f-wqw6lxQ",
+			"type": "Organization"
 		}
 	]
 }
 ```
 ### technographics
-  
+  Technologies used by this organization.
 * **Type:** Technographics
 * **Example:**
 ```
@@ -1504,16 +2256,43 @@ Note that certain longer field examples may be truncated for readability.
 	"technographics": [
 		{
 			"technology": {
-				"recordId": "EPdsrDmLiMQCskvBLp_dloQ@735",
-				"name": "salesforce",
-				"surfaceForm": "salesforce",
-				"position": "companyTechnographicsTechnology",
+				"name": "TrustArc",
 				"type": "DiffbotEntity"
-			}
+			},
+			"categories": [
+				"Cookie compliance"
+			]
+		},
+		{
+			"technology": {
+				"name": "Tealium AudienceStream",
+				"type": "DiffbotEntity"
+			},
+			"categories": [
+				"Segmentation"
+			]
+		},
+		{
+			"technology": {
+				"name": "Linkedin Insight Tag",
+				"type": "DiffbotEntity"
+			},
+			"categories": [
+				"Analytics"
+			]
 		}
 	]
 }
 ```
+### thaiTaxpayerIds
+  Unique taxpayer number for company in Thailand, also known as company registration number.
+* **Type:** String
+* **Example:**
+```
+{
+	"thaiTaxpayerIds": ""
+}
+```
 ### totalInvestment
   Sum of all investments.
 * **Type:** Amount
@@ -1526,13 +2305,62 @@ Note that certain longer field examples may be truncated for readability.
 	}
 }
 ```
+### tsicClassification
+  Thailand Standard Industrial Classification (TSIC).
+* **Type:** ClassificationCode
+* **Example:**
+```
+{
+	"tsicClassification": [
+		{
+			"code": "",
+			"level": 0,
+			"isPrimary": false,
+			"name": "",
+			"diffbotUri": "",
+			"version": ""
+		}
+	]
+}
+```
 ### twitterUri
-  Link to the LinkedIn profile of this entity
+  Link to the Twitter profile of this entity
 * **Type:** URL
 * **Example:**
 ```
 {
-	"twitterUri": "twitter.com/IBM"
+	"twitterUri": "twitter.com/ibm"
+}
+```
+### type
+  The top-level type of a Diffbot entity. Examples of type include Person, Organization, Article, Product.
+* **Type:** Type
+* **Example:**
+```
+{
+	"type": "Organization"
+}
+```
+### types
+  All types of a Diffbot entity, including the value of the field &#39;type&#39;.
+* **Type:** String
+* **Example:**
+```
+{
+	"types": [
+		"Organization",
+		"Corporation",
+		"Company"
+	]
+}
+```
+### uenNumbers
+  Unique Entity Number (UEN) is a business identification number in Singapore.
+* **Type:** String
+* **Example:**
+```
+{
+	"uenNumbers": ""
 }
 ```
 ### ukSicClassification
@@ -1544,20 +2372,99 @@ Note that certain longer field examples may be truncated for readability.
 	"ukSicClassification": [
 		{
 			"code": "",
+			"level": 0,
 			"isPrimary": false,
 			"name": "",
+			"diffbotUri": "",
 			"version": ""
 		}
 	]
 }
 ```
+### ultimateParent
+  The ultimate parent company of this subsidiary.
+* **Type:** LinkedEntity
+* **Example:**
+```
+{
+	"ultimateParent": {
+		"types": [
+			"Organization",
+			"Corporation",
+			"Company"
+		],
+		"name": "IBM (United States)",
+		"diffbotUri": "http://diffbot.com/entity/E2dnSQGS6MQSUsS8cWvJ4xg",
+		"targetDiffbotId": "E2dnSQGS6MQSUsS8cWvJ4xg",
+		"type": "Organization"
+	}
+}
+```
 ### vatIdentificationNumbers
   VAT identification number, an identifier used in many countries, including the countries of the European Union, for value added tax purposes
 * **Type:** String
 * **Example:**
 ```
 {
-	"vatIdentificationNumbers": ""
+	"vatIdentificationNumbers": [
+		"IN29980271267",
+		"FR20890677800",
+		"130871985"
+	]
+}
+```
+### wikipediaPageviews
+  The number of views of its Wikipedia page of the last month if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviews": 199993
+}
+```
+### wikipediaPageviewsGrowth
+  The month over month growth of wikipediaPageviews, where we count the increment of the number of page views of the second to last (full) month, compared with that of the last (full) month. if today was Aug 16th, 2022, the last complete month is July. So it refers to the increment from June to July, i.e., ( f(July) - f(June) ) ÷ f(June) x 100%. The f(.) only counts the first 28 days of a month, to avoid fluctuations between 31-days months like Jan and 28(29)-days months like Feb.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsGrowth": 0.017025605
+}
+```
+### wikipediaPageviewsLastQuarter
+  The number of views of its Wikipedia page of the last quarter if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastQuarter": 600651
+}
+```
+### wikipediaPageviewsLastQuarterGrowth
+  The quarter over quarter growth of wikipediaPageviews, where we count the increment of the number of page views of the second to last (full) quarter, compared with that of the last (full) quarter. If today was Aug 16th, 2022, the last complete quarter is Q2 (April, May, June). So it refers to the increment from Q1 to Q2, i.e., ( f(Q2) - f(Q1) ) ÷ f(Q1) x 100%.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastQuarterGrowth": 0.06729652
+}
+```
+### wikipediaPageviewsLastYear
+  The number of views of its Wikipedia page of the last year if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastYear": 2656578
+}
+```
+### wikipediaPageviewsLastYearGrowth
+  The year over year growth of wikipediaPageviews, where we count the monthly-rolling increment of the year before last than the last year. It today was Aug 16th, 2022, it is computed by comparing the numbers from Aug 2021 to July 2022 and from Aug 2020 to July 2021, i.e., ( f(Aug 2021 to July 2022) - f(Aug 2020 to July 2021) ) ÷ f(Aug 2020 to July 2021) x 100%.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastYearGrowth": 0.052473985
 }
 ```
 ### wikipediaUri
@@ -1570,7 +2477,7 @@ Note that certain longer field examples may be truncated for readability.
 }
 ```
 ### yearlyRevenues
-  An organization&#39;s revenue for a period of 12 months.
+  An organization&#39;s officially reported revenue for a period of 12 months.
 * **Type:** YearlyRevenue
 * **Example:**
 ```
@@ -1579,36 +2486,26 @@ Note that certain longer field examples may be truncated for readability.
 		{
 			"revenue": {
 				"currency": "USD",
-				"value": 73620000000
+				"value": 62800000000
 			},
 			"isCurrent": false,
-			"year": 2020
+			"year": 2025
 		},
 		{
 			"revenue": {
 				"currency": "USD",
-				"value": 79591000000
+				"value": 62753000000
 			},
 			"isCurrent": false,
-			"year": 2018
+			"year": 2024
 		},
 		{
 			"revenue": {
 				"currency": "USD",
-				"value": 77147000000
+				"value": 61860000000
 			},
 			"isCurrent": false,
-			"year": 2019,
-			"filingDate": {
-				"str": "d2021-02-23",
-				"precision": 3,
-				"timestamp": 1614038400000
-			},
-			"revenueDate": {
-				"str": "d2019-12-31",
-				"precision": 3,
-				"timestamp": 1577750400000
-			}
+			"year": 2023
 		}
 	]
 }
diff --git a/docs/kg-ont-person.md b/docs/kg-ont-person.md
index 5c17b2d9..b521a21c 100644
--- a/docs/kg-ont-person.md
+++ b/docs/kg-ont-person.md
@@ -1,16 +1,28 @@
 ---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
 id: kg-ont-person
 title: Person
+generatedBy: generateOntology.js
 ---
 
 The person entity type encompasses all people known to the Knowledge Graph. 
 
 Note that fields are not guaranteed to exist in every entity record.
 
->New to the Diffbot Knowledge Graph? [Start here](dql-quickstart).
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
 
 ## Person Fields
 * [age](#age) 
+* [allDescriptions](#alldescriptions) 
+* [allNames](#allnames) 
+* [allOriginHashes](#alloriginhashes) 
+* [allUriDetails](#alluridetails) 
+* [allUris](#alluris) 
 * [angellistUri](#angellisturi) 
 * [articles](#articles) 
 * [awards](#awards) 
@@ -20,40 +32,63 @@ Note that fields are not guaranteed to exist in every entity record.
 * [children](#children) 
 * [colleagues](#colleagues) 
 * [connectedIndustries](#connectedindustries) 
+* [crawlTimestamp](#crawltimestamp) 
 * [crunchbaseUri](#crunchbaseuri) 
 * [deathDate](#deathdate) 
 * [deathPlace](#deathplace) 
+* [description](#description) 
+* [descriptors](#descriptors) 
+* [diffbotUri](#diffboturi) 
 * [educations](#educations) 
 * [emailAddresses](#emailaddresses) 
 * [employments](#employments) 
 * [eyeColor](#eyecolor) 
 * [facebookUri](#facebookuri) 
-* [friends](#friends) 
 * [gender](#gender) 
 * [githubUri](#githuburi) 
 * [googlePlusUri](#googleplusuri) 
-* [hairColor](#haircolor) 
 * [height](#height) 
 * [homepageUri](#homepageuri) 
+* [id](#id) 
+* [image](#image) 
+* [images](#images) 
+* [importance](#importance) 
 * [instagramUri](#instagramuri) 
 * [interests](#interests) 
 * [languages](#languages) 
 * [linkedInUri](#linkedinuri) 
 * [location](#location) 
 * [locations](#locations) 
+* [name](#name) 
 * [nameDetail](#namedetail) 
 * [nationalities](#nationalities) 
+* [nbFollowers](#nbfollowers) 
+* [nbIncomingEdges](#nbincomingedges) 
+* [nbOrigins](#nborigins) 
 * [netWorth](#networth) 
+* [nonCanonicalFacts](#noncanonicalfacts) 
+* [npiNumbers](#npinumbers) 
+* [originDetails](#origindetails) 
+* [origins](#origins) 
 * [parents](#parents) 
 * [phoneNumbers](#phonenumbers) 
 * [politicalAffiliation](#politicalaffiliation) 
-* [posts](#posts) 
 * [religion](#religion) 
+* [sepMexicoIds](#sepmexicoids) 
 * [siblings](#siblings) 
 * [skills](#skills) 
+* [summary](#summary) 
 * [twitterUri](#twitteruri) 
+* [type](#type) 
+* [types](#types) 
 * [unions](#unions) 
 * [weight](#weight) 
+* [wikipediaPageviews](#wikipediapageviews) 
+* [wikipediaPageviewsGrowth](#wikipediapageviewsgrowth) 
+* [wikipediaPageviewsLastQuarter](#wikipediapageviewslastquarter) 
+* [wikipediaPageviewsLastQuarterGrowth](#wikipediapageviewslastquartergrowth) 
+* [wikipediaPageviewsLastYear](#wikipediapageviewslastyear) 
+* [wikipediaPageviewsLastYearGrowth](#wikipediapageviewslastyeargrowth) 
 * [wikipediaUri](#wikipediauri) 
 * [youtubeUri](#youtubeuri) 
 
@@ -66,7 +101,82 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"age": 76
+	"age": 80
+}
+```
+### allDescriptions
+  All descriptions found for this entity. For the best description, refer to the field &#39;description&#39;.
+* **Type:** String
+* **Example:**
+```
+{
+	"allDescriptions": [
+		"Thomas Edgar Wheeler (born April 5, 1946) is an American businessman and former government official. A member of the Democratic Party, he served as the 31st Chairman of the Federal Communications Commission.",
+		"Tom Wheeler is the current Chairman at Alef. Prior to this, they were Managing Director at Core Capital Partners, President/CEO of the Cellular Telecommunications & Internet Association, and Chairman of the Federal Communications Commission. Tom has also held positions at Harvard Kennedy School and Harvard Law School. Tom Wheeler attended The Ohio State University, where they studied international trade.",
+		"Tom Wheeler is the Managing Director of Core Capital Partners. He previously worked at FCC as a Chairman. Tom Wheeler attended The Ohio State University."
+	]
+}
+```
+### allNames
+  All names used, including nicknames, full names and transliterations to other languages.
+* **Type:** String
+* **Example:**
+```
+{
+	"allNames": [
+		"Tom Wheeler",
+		"Том Вилер",
+		"汤姆·惠勒"
+	]
+}
+```
+### allOriginHashes
+  For Diffbot&#39;s internal use only.
+* **Type:** String
+* **Example:**
+```
+{
+	"allOriginHashes": [
+		"Tc5u2UoRP0iZY1D1f79u7Q",
+		"SDAaBzTNN5mysszerQ1VNg",
+		"3GudoNIfOaWgx29PAPZ2zA"
+	]
+}
+```
+### allUriDetails
+  Additional information about each URI in &#39;allUris&#39;, which lists the URIs associated with this entity.
+* **Type:** UriDetails
+* **Example:**
+```
+{
+	"allUriDetails": [
+		{
+			"domainMonthlyTrafficGrowth": "",
+			"domainMonthlyTraffic": 0,
+			"redirectsTo": "",
+			"nbFollowing": 0,
+			"uriType": "",
+			"verified": false,
+			"nbLinkedAccounts": 0,
+			"nbFollowers": 0,
+			"httpCodeTimestamp": 0,
+			"httpCode": "",
+			"uri": ""
+		}
+	]
+}
+```
+### allUris
+  All URIs associated with an entity. A URI (uniform resource identifier) is a page on the web that describes an entity (e.g., an company&#39;s homepage or a person&#39;s social network profile).
+* **Type:** URL
+* **Example:**
+```
+{
+	"allUris": [
+		"bloomberg.com/profile/person/2045213",
+		"bloomberg.com/profiles/people/2045213-thomas-e-wheeler",
+		"bloomberg.com/profiles/people/2045213-thomas-wheeler"
+	]
 }
 ```
 ### angellistUri
@@ -86,33 +196,15 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"articles": [
 		{
-			"recordId": "EEIzhzuLVPeKuQ7KjPSa6aQ@289",
-			"name": "Take Command: Leadership Lessons from the Civil War // Doubleday",
-			"websiteUris": [
-				"civilwarleadership.com"
-			],
-			"surfaceForm": "Take Command: Leadership Lessons from the Civil War // Doubleday",
-			"position": "personArticles",
+			"name": "Mr. Lincoln's T-Mails: The Untold Story of How Abraham Lincoln Used the Telegraph to Win the Civil War // 2006 HarperCollins -",
 			"type": "Article"
 		},
 		{
-			"recordId": "EEIzhzuLVPeKuQ7KjPSa6aQ@288",
-			"name": "Mr. Lincoln's T-Mails: The Untold Story of How Abraham Lincoln Used the Telegraph to Win the Civil War // HarperCollins",
-			"websiteUris": [
-				"mrlincolnstmails.com"
-			],
-			"surfaceForm": "Mr. Lincoln's T-Mails: The Untold Story of How Abraham Lincoln Used the Telegraph to Win the Civil War // HarperCollins",
-			"position": "personArticles",
+			"name": "Take Command: Leadership Lessons from the Civil War // 2000 Doubleday -",
 			"type": "Article"
 		},
 		{
-			"recordId": "EEIzhzuLVPeKuQ7KjPSa6aQ@290",
-			"name": "Mr. Lincoln's T-Mails: The Untold Story of How Abraham Lincoln Used the Telegraph to Win the Civil War // HarperCollins 2006",
-			"websiteUris": [
-				"linkedin.com/redir/redirect"
-			],
-			"surfaceForm": "Mr. Lincoln's T-Mails: The Untold Story of How Abraham Lincoln Used the Telegraph to Win the Civil War // HarperCollins 2006",
-			"position": "personArticles",
+			"name": "From Gutenberg to Google: The History of Our Future // Brookings Institution Press February 26, 2019 -",
 			"type": "Article"
 		}
 	]
@@ -157,62 +249,74 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"birthPlace": {
 		"country": {
-			"summary": "Sovereign state in North America",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEQ%3El%601Nw%7BM0Bf7hu7z%3FRe9s4XwGXedrKUAN%28%3D%5ECHnM%60%29.%7BOV",
+			"summary": "Country located primarily in North America",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ",
 			"types": [
 				"Place",
-				"AdministrativeArea"
+				"AdministrativeArea",
+				"Country"
 			],
-			"name": "United States of America",
+			"name": "United States",
 			"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
-			"targetDiffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
 			"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
-			"type": "AdministrativeArea"
+			"type": "Place"
 		},
 		"isCurrent": false,
-		"address": "Redlands, California",
+		"address": "Redlands, California, United States",
 		"city": {
 			"summary": "City in San Bernardino County, California, United States",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FCvrv%3ExO%3ALE1l9Bl%3Cb%7DGej%5C%7BRyDCUDe%7BV0I%5E7Pdgj0RnJj3%3B%7C%3ESgGu1EiSd2U2Kb%3FchDc3D_NbtOi%7DVnTj%3DL9FE%2F%5B%7DG%5D9%5B%7D7d.ZvE",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FevDr%3EhV%7D%5Dh8%2Cz6YGknz%2C6%3FkHq%7CRvV%2Cq3R6r-p9%7D%28Og5_1D%5D9Zo9%29f%28I6Tk4Ww%29.%3Aan",
 			"types": [
 				"Place",
-				"AdministrativeArea"
+				"AdministrativeArea",
+				"City"
 			],
 			"name": "Redlands",
 			"diffbotUri": "http://diffbot.com/entity/EEGqoBftsOZyh3_RKbQE3mw",
-			"targetDiffbotUri": "http://diffbot.com/entity/EEGqoBftsOZyh3_RKbQE3mw",
 			"targetDiffbotId": "EEGqoBftsOZyh3_RKbQE3mw",
-			"type": "AdministrativeArea"
+			"type": "Place"
+		},
+		"metroArea": {
+			"summary": "Metropolitan area and region in Southern California, United States",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FDvsq%3ExP%7Bo3L%7EzEn7lzQr%40%5BkC5Kjs.c2W",
+			"types": [
+				"Place",
+				"AdministrativeArea"
+			],
+			"name": "Inland Empire",
+			"diffbotUri": "http://diffbot.com/entity/EfvaXmNJePu-q6vYkH_619Q",
+			"targetDiffbotId": "EfvaXmNJePu-q6vYkH_619Q",
+			"type": "Place"
 		},
 		"subregion": {
 			"summary": "County in California, United States",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGu%3ErO%3CLr2Y%5EBfA_%7EJt%40NeLn2L%7EL%60zdzEW%7DBf%3C%5B_HnH%5C3%3EqG%5EgyvBT8%5E.7hz",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FBvqt%3ExS%7DYb%3B%60z4%5BFXQ%3DxENxHn9Sqvh7%5E5P%2C%7D2f%3Ae3RnHdr.%7BOV",
 			"types": [
 				"Place",
-				"AdministrativeArea"
+				"AdministrativeArea",
+				"Subregion"
 			],
 			"name": "San Bernardino County",
 			"diffbotUri": "http://diffbot.com/entity/EApueG2dHP3iRBLbjF2w2gQ",
-			"targetDiffbotUri": "http://diffbot.com/entity/EApueG2dHP3iRBLbjF2w2gQ",
 			"targetDiffbotId": "EApueG2dHP3iRBLbjF2w2gQ",
-			"type": "AdministrativeArea"
+			"type": "Place"
 		},
 		"latitude": 34.04679489135742,
 		"precision": 9.702208518981934,
 		"postalCode": "92374",
-		"surfaceForm": "Redlands, California",
+		"surfaceForm": "Redlands, California, United States",
 		"region": {
 			"summary": "State of the United States of America",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3Fav%40T%3ExS%7DYb%3B%60zt%5BDbuGxEVg.xAK",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FEvtr%3EnAo-8UY%5EBfA_%7EJt%40N%2CCS0ZsGZqQ%2F%3BO%3C%5EwBd2Uj9HvRq%3C%5E.Pw4",
 			"types": [
 				"Place",
-				"AdministrativeArea"
+				"AdministrativeArea",
+				"Region"
 			],
 			"name": "California",
 			"diffbotUri": "http://diffbot.com/entity/El0_8ehooNxOPT36Y4RdV9w",
-			"targetDiffbotUri": "http://diffbot.com/entity/El0_8ehooNxOPT36Y4RdV9w",
 			"targetDiffbotId": "El0_8ehooNxOPT36Y4RdV9w",
-			"type": "AdministrativeArea"
+			"type": "Place"
 		},
 		"longitude": -117.17427062988281
 	}
@@ -247,11 +351,8 @@ Note that certain longer field examples may be truncated for readability.
 				}
 			],
 			"types": "",
-			"websiteUris": "",
 			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
+			"name": ""
 		}
 	]
 }
@@ -275,7 +376,7 @@ Note that certain longer field examples may be truncated for readability.
 				"precision": 0,
 				"timestamp": 0
 			},
-			"relationship": "",
+			"relationship": {},
 			"colleague": {
 				"summary": "",
 				"image": "",
@@ -289,11 +390,8 @@ Note that certain longer field examples may be truncated for readability.
 					}
 				],
 				"types": "",
-				"websiteUris": "",
 				"diffbotUri": "",
-				"name": "",
-				"targetDiffbotUri": "",
-				"surfaceForm": ""
+				"name": ""
 			}
 		}
 	]
@@ -305,7 +403,16 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"connectedIndustries": []
+	"connectedIndustries": {}
+}
+```
+### crawlTimestamp
+  The default crawlTimestamp is the most recent date of all of the crawlTimestamps of the origins used to compute the Entity, returned as a UNIX time.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"crawlTimestamp": 1757054954
 }
 ```
 ### crunchbaseUri
@@ -351,11 +458,8 @@ Note that certain longer field examples may be truncated for readability.
 				}
 			],
 			"types": "",
-			"websiteUris": "",
 			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
+			"name": ""
 		},
 		"address": "",
 		"city": {
@@ -371,11 +475,8 @@ Note that certain longer field examples may be truncated for readability.
 				}
 			],
 			"types": "",
-			"websiteUris": "",
 			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
+			"name": ""
 		},
 		"subregion": {
 			"summary": "",
@@ -390,18 +491,22 @@ Note that certain longer field examples may be truncated for readability.
 				}
 			],
 			"types": "",
-			"websiteUris": "",
 			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
+			"name": ""
 		},
 		"latitude": "",
 		"precision": "",
 		"postalCode": "",
+		"locationType": [],
 		"surfaceForm": "",
 		"poBox": "",
 		"isCurrent": false,
+		"estimatedValue": {
+			"currency": "",
+			"value": ""
+		},
+		"occupancyType": "",
+		"isPrimary": false,
 		"street": "",
 		"metroArea": {
 			"summary": "",
@@ -416,11 +521,12 @@ Note that certain longer field examples may be truncated for readability.
 				}
 			],
 			"types": "",
-			"websiteUris": "",
 			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
+			"name": ""
+		},
+		"estimatedEquity": {
+			"currency": "",
+			"value": ""
 		},
 		"region": {
 			"summary": "",
@@ -435,11 +541,8 @@ Note that certain longer field examples may be truncated for readability.
 				}
 			],
 			"types": "",
-			"websiteUris": "",
 			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
+			"name": ""
 		},
 		"rawAdministrativeArea": {
 			"summary": "",
@@ -454,16 +557,40 @@ Note that certain longer field examples may be truncated for readability.
 				}
 			],
 			"types": "",
-			"websiteUris": "",
 			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
+			"name": ""
 		},
 		"longitude": ""
 	}
 }
 ```
+### description
+  A few sentences describing an entity
+* **Type:** String
+* **Example:**
+```
+{
+	"description": "Tom Wheeler is the current Chairman at Alef. Prior to this, they were Managing Director at Core Capital Partners, President/CEO of the Cellular Telecommunications & Internet Association, and Chairman of the Federal Communications Commission. Tom has also held positions at Harvard Kennedy School and Harvard Law School. Tom Wheeler attended The Ohio State University, where they studied international trade."
+}
+```
+### descriptors
+  A list of free-form keywords describing this entity
+* **Type:** String
+* **Example:**
+```
+{
+	"descriptors": ""
+}
+```
+### diffbotUri
+  diffbotUri is the URI an entity&#39;s  (URI), which is defined by appending the Diffbot ID to the URL https:&#x2F;&#x2F;diffbot.com&#x2F;entity&#x2F;. For example, Diffbot&#39;s entityID is CWSwJ_SWQPfqO3HQsxY4lGg and its DiffbotUri is https:&#x2F;&#x2F;diffbot.com&#x2F;entity&#x2F;CWSwJ_SWQPfqO3HQsxY4lGg
+* **Type:** URL
+* **Example:**
+```
+{
+	"diffbotUri": "http://diffbot.com/entity/EEIzhzuLVPeKuQ7KjPSa6aQ"
+}
+```
 ### educations
   Education history.
 * **Type:** Education
@@ -474,21 +601,22 @@ Note that certain longer field examples may be truncated for readability.
 		{
 			"institution": {
 				"summary": "Public research university in Columbus, Ohio, United States",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FGvvO%3EtV5%5Cbon%7CU_7N%7DA%7C%3C_yMyDCzRk%7Bj0Ed%2F%5Bd%3Ak4R.Mqx",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0Stn8p.%5DjEp9G.Bd%7Bk%40UuPNeL%7D-Dz_z-Ze%3Bn-kiKc-b%5Dvv%3FURLN8U%7CzN_%3Cb4E.A%5Dm",
 				"types": [
-					"Organization"
+					"Organization",
+					"Corporation",
+					"Company",
+					"OrganizationInvestor"
 				],
-				"name": "The Ohio State University",
+				"name": "Ohio State University",
 				"diffbotUri": "http://diffbot.com/entity/EXqnLTSovNzi-4KlIxjHhyA",
-				"targetDiffbotUri": "http://diffbot.com/entity/EXqnLTSovNzi-4KlIxjHhyA",
 				"targetDiffbotId": "EXqnLTSovNzi-4KlIxjHhyA",
-				"surfaceForm": "The Ohio State University",
 				"type": "Organization"
 			},
 			"isCurrent": false,
 			"major": {
-				"name": "International Trade",
-				"surfaceForm": "International Trade"
+				"name": "Business, International Trade",
+				"type": "EducationMajorEntity"
 			},
 			"degree": {
 				"types": [
@@ -497,9 +625,38 @@ Note that certain longer field examples may be truncated for readability.
 				],
 				"name": "Bachelor's (4 year program)",
 				"diffbotUri": "http://diffbot.com/entity/EtWuqNi7UOGu2JRK_z95kDg",
-				"targetDiffbotUri": "http://diffbot.com/entity/EtWuqNi7UOGu2JRK_z95kDg",
 				"targetDiffbotId": "EtWuqNi7UOGu2JRK_z95kDg",
-				"surfaceForm": "Bachelor's (4 year program)",
+				"type": "DegreeEntity"
+			},
+			"from": {
+				"str": "d1964-XX-XX",
+				"precision": 1,
+				"timestamp": -189388800000
+			},
+			"to": {
+				"str": "d1968-XX-XX",
+				"precision": 1,
+				"timestamp": -63158400000
+			}
+		},
+		{
+			"institution": {
+				"summary": "Public research university in Columbus, Ohio, United States",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0Stn8p.%5DjEp9G.Bd%7Bk%40UuPNeL%7D-Dz_z-Ze%3Bn-kiKc-b%5Dvv%3FURLN8U%7CzN_%3Cb4E.A%5Dm",
+				"types": [
+					"Organization",
+					"Corporation",
+					"Company",
+					"OrganizationInvestor"
+				],
+				"name": "Ohio State University",
+				"diffbotUri": "http://diffbot.com/entity/EXqnLTSovNzi-4KlIxjHhyA",
+				"targetDiffbotId": "EXqnLTSovNzi-4KlIxjHhyA",
+				"type": "Organization"
+			},
+			"isCurrent": false,
+			"degree": {
+				"name": "International Trade",
 				"type": "DegreeEntity"
 			},
 			"from": {
@@ -540,64 +697,71 @@ Note that certain longer field examples may be truncated for readability.
 		{
 			"isCurrent": true,
 			"employer": {
-				"summary": "Organization based in United States",
+				"summary": "Lifestyle experience provider",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0Stn8p.%5DjEp9G.Bd%7BkBXpJP1K%2F-_1%5BZ-Zg6q-j4Rk-E%7CIosYv0pgO1zN_%3Cb4E.A%5Dm",
 				"types": [
 					"Organization",
-					"LocalBusiness",
-					"Place"
+					"Corporation",
+					"Company"
 				],
-				"name": "Shiloh Group",
-				"diffbotUri": "http://diffbot.com/entity/ELF4ccy36PMug3N0XWxDdrg",
-				"targetDiffbotUri": "http://diffbot.com/entity/ELF4ccy36PMug3N0XWxDdrg",
-				"targetDiffbotId": "ELF4ccy36PMug3N0XWxDdrg",
-				"surfaceForm": "Shiloh Group",
-				"type": "LocalBusiness"
+				"name": "Alef Group",
+				"diffbotUri": "http://diffbot.com/entity/EGqlO7Wv1NbKOXE9teORnEg",
+				"targetDiffbotId": "EGqlO7Wv1NbKOXE9teORnEg",
+				"type": "Organization"
 			},
 			"from": {
-				"str": "d2003-07-XX",
-				"precision": 2,
-				"timestamp": 1057017600000
+				"str": "d2022-05-01",
+				"precision": 3,
+				"timestamp": 1651363200000
 			},
 			"categories": [
 				{
-					"name": "Chief Officer",
-					"diffbotUri": "http://diffbot.com/entity/ETONJ_vUmODK7D7WTWa6OhA",
-					"targetDiffbotUri": "http://diffbot.com/entity/ETONJ_vUmODK7D7WTWa6OhA",
-					"targetDiffbotId": "ETONJ_vUmODK7D7WTWa6OhA",
+					"types": [
+						"Intangible",
+						"EmploymentCategory"
+					],
+					"name": "Board Member",
+					"diffbotUri": "http://diffbot.com/entity/EnC5drWy1NVuOGQHd2ll0xw",
+					"targetDiffbotId": "EnC5drWy1NVuOGQHd2ll0xw",
 					"type": "EmploymentCategory"
 				},
 				{
+					"types": [
+						"Intangible",
+						"EmploymentCategory"
+					],
 					"name": "Management",
 					"diffbotUri": "http://diffbot.com/entity/EpXGc9jmNPQW3wt-ny5SqCQ",
-					"targetDiffbotUri": "http://diffbot.com/entity/EpXGc9jmNPQW3wt-ny5SqCQ",
 					"targetDiffbotId": "EpXGc9jmNPQW3wt-ny5SqCQ",
 					"type": "EmploymentCategory"
 				},
 				{
+					"types": [
+						"Intangible",
+						"EmploymentCategory"
+					],
 					"name": "Executive",
 					"diffbotUri": "http://diffbot.com/entity/EFHD6pfzYMtqdaaytNomkhA",
-					"targetDiffbotUri": "http://diffbot.com/entity/EFHD6pfzYMtqdaaytNomkhA",
 					"targetDiffbotId": "EFHD6pfzYMtqdaaytNomkhA",
 					"type": "EmploymentCategory"
 				}
 			],
-			"title": "President/CEO"
+			"title": "Board Member"
 		},
 		{
 			"isCurrent": true,
 			"employer": {
-				"summary": "Financial services company founded in 1999",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St%7D9u.LnOv%7BI%7C%40g7.pBYINs%3Ff%7CGZ7jr-tGZhWf%3DK%2FOvy%5Bp%3CSKbs8i%7CEyNzBa%3DXt%3Ek5KcBD0vSA%5EvRq%3D0%5DUd%60%402r%3Fm%3BQ9H%3DTmJF%5DG.zBX",
+				"summary": "M&A advisory firm",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0SttV.LYeDo.C%7DLtpX%7C5k%7EO2%7CZPcZ%3CZs%3B6UP5H5OEsdZAwt%3BPMneU1%2Fj%2F%60%5B%3F%3B",
 				"types": [
 					"Organization",
-					"Corporation"
+					"Corporation",
+					"Company"
 				],
-				"name": "Core Capital Partners",
-				"diffbotUri": "http://diffbot.com/entity/ErLfevHY1MzaATmqeEbm4AQ",
-				"targetDiffbotUri": "http://diffbot.com/entity/ErLfevHY1MzaATmqeEbm4AQ",
-				"targetDiffbotId": "ErLfevHY1MzaATmqeEbm4AQ",
-				"surfaceForm": "Core Capital Partners",
-				"type": "Corporation"
+				"name": "Core Capital Group",
+				"diffbotUri": "http://diffbot.com/entity/EfSccRU7EOpSsVPU9m73bLg",
+				"targetDiffbotId": "EfSccRU7EOpSsVPU9m73bLg",
+				"type": "Organization"
 			},
 			"from": {
 				"str": "d2005-01-XX",
@@ -606,23 +770,32 @@ Note that certain longer field examples may be truncated for readability.
 			},
 			"categories": [
 				{
+					"types": [
+						"Intangible",
+						"EmploymentCategory"
+					],
 					"name": "Management",
 					"diffbotUri": "http://diffbot.com/entity/EpXGc9jmNPQW3wt-ny5SqCQ",
-					"targetDiffbotUri": "http://diffbot.com/entity/EpXGc9jmNPQW3wt-ny5SqCQ",
 					"targetDiffbotId": "EpXGc9jmNPQW3wt-ny5SqCQ",
 					"type": "EmploymentCategory"
 				},
 				{
+					"types": [
+						"Intangible",
+						"EmploymentCategory"
+					],
 					"name": "Shareholder",
 					"diffbotUri": "http://diffbot.com/entity/EnjEbsIYNORq7LaLzpGLaeg",
-					"targetDiffbotUri": "http://diffbot.com/entity/EnjEbsIYNORq7LaLzpGLaeg",
 					"targetDiffbotId": "EnjEbsIYNORq7LaLzpGLaeg",
 					"type": "EmploymentCategory"
 				},
 				{
+					"types": [
+						"Intangible",
+						"EmploymentCategory"
+					],
 					"name": "Executive",
 					"diffbotUri": "http://diffbot.com/entity/EFHD6pfzYMtqdaaytNomkhA",
-					"targetDiffbotUri": "http://diffbot.com/entity/EFHD6pfzYMtqdaaytNomkhA",
 					"targetDiffbotId": "EFHD6pfzYMtqdaaytNomkhA",
 					"type": "EmploymentCategory"
 				}
@@ -632,43 +805,51 @@ Note that certain longer field examples may be truncated for readability.
 		{
 			"isCurrent": true,
 			"employer": {
-				"summary": "Boston, Massachusetts–based software company that produces an online video platform",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St%7D9u.LnOv%7BI%7C%40g7.pBYINs%3Ff%7CGZ7jr-tGZhWf%3DK%2FOvy%5Bp%3CSKbs8i%7CEyO2%40%3F0FW9LpRQJSk8%5E5Jh",
+				"summary": "Drone airspace management platform",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0Stn8p.%5DjEp9G.Bd%7Bkn8rRrb%7D%2F-%6008y-Ze%3Br-CdPG-B%7C%40pAYpOp4N%5BzN_%3Cb4E.A%5Dm",
 				"types": [
 					"Organization",
-					"Corporation"
+					"Corporation",
+					"Company"
 				],
-				"name": "Brightcove, Inc.",
-				"diffbotUri": "http://diffbot.com/entity/ExQ62VDi-OvWQ3qO1NhflJA",
-				"targetDiffbotUri": "http://diffbot.com/entity/ExQ62VDi-OvWQ3qO1NhflJA",
-				"targetDiffbotId": "ExQ62VDi-OvWQ3qO1NhflJA",
-				"surfaceForm": "Brightcove, Inc.",
-				"type": "Corporation"
+				"name": "AirMap",
+				"diffbotUri": "http://diffbot.com/entity/E66uGQYwVOYiNi050NUhhHw",
+				"targetDiffbotId": "E66uGQYwVOYiNi050NUhhHw",
+				"type": "Organization"
 			},
 			"from": {
-				"str": "d2018-04-XX",
+				"str": "d2019-06-XX",
 				"precision": 2,
-				"timestamp": 1522540800000
+				"timestamp": 1559347200000
 			},
 			"categories": [
 				{
+					"types": [
+						"Intangible",
+						"EmploymentCategory"
+					],
 					"name": "Management",
 					"diffbotUri": "http://diffbot.com/entity/EpXGc9jmNPQW3wt-ny5SqCQ",
-					"targetDiffbotUri": "http://diffbot.com/entity/EpXGc9jmNPQW3wt-ny5SqCQ",
 					"targetDiffbotId": "EpXGc9jmNPQW3wt-ny5SqCQ",
 					"type": "EmploymentCategory"
 				},
 				{
+					"types": [
+						"Intangible",
+						"EmploymentCategory"
+					],
 					"name": "Board Member",
 					"diffbotUri": "http://diffbot.com/entity/EnC5drWy1NVuOGQHd2ll0xw",
-					"targetDiffbotUri": "http://diffbot.com/entity/EnC5drWy1NVuOGQHd2ll0xw",
 					"targetDiffbotId": "EnC5drWy1NVuOGQHd2ll0xw",
 					"type": "EmploymentCategory"
 				},
 				{
+					"types": [
+						"Intangible",
+						"EmploymentCategory"
+					],
 					"name": "Executive",
 					"diffbotUri": "http://diffbot.com/entity/EFHD6pfzYMtqdaaytNomkhA",
-					"targetDiffbotUri": "http://diffbot.com/entity/EFHD6pfzYMtqdaaytNomkhA",
 					"targetDiffbotId": "EFHD6pfzYMtqdaaytNomkhA",
 					"type": "EmploymentCategory"
 				}
@@ -684,7 +865,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"eyeColor": ""
+	"eyeColor": {}
 }
 ```
 ### facebookUri
@@ -696,44 +877,13 @@ Note that certain longer field examples may be truncated for readability.
 	"facebookUri": ""
 }
 ```
-### friends
-  This person&#39;s friends.
-* **Type:** LinkedEntity
-* **Example:**
-```
-{
-	"friends": [
-		{
-			"summary": "",
-			"image": "",
-			"images": [
-				{
-					"classifications": "",
-					"fingerprint": "",
-					"title": "",
-					"isCached": false,
-					"url": ""
-				}
-			],
-			"types": "",
-			"websiteUris": "",
-			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
-		}
-	]
-}
-```
 ### gender
   A person&#39;s gender.
 * **Type:** Gender
 * **Example:**
 ```
 {
-	"gender": {
-		"normalizedValue": "Male"
-	}
+	"gender": {}
 }
 ```
 ### githubUri
@@ -754,15 +904,6 @@ Note that certain longer field examples may be truncated for readability.
 	"googlePlusUri": ""
 }
 ```
-### hairColor
-  This person&#39;s hair color.
-* **Type:** HairColor
-* **Example:**
-```
-{
-	"hairColor": ""
-}
-```
 ### height
   This person&#39;s height in meters.
 * **Type:** Float
@@ -781,6 +922,55 @@ Note that certain longer field examples may be truncated for readability.
 	"homepageUri": "fcc.gov/leadership/tom-wheeler"
 }
 ```
+### id
+  An alphanumeric string like CWSwJ_SWQPfqO3HQsxY4lGg that uniquely identifies an entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"id": "EEIzhzuLVPeKuQ7KjPSa6aQ"
+}
+```
+### image
+  The main image used to represent the entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"image": "https://kg.diffbot.com/image/api/get?fetch=yes&urls=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FEvtt%3Ey%5D9LZ4_0M_JX%7E%3El%40PoEqzTzRm1.%7BGW,g%3Cj7P0Stn8p.%5DjEp9G.Bd%7BkqXrSQgKx-h%2FYZ-Z8%5Dp-D%3B%7Cd-j%7DAQGVT%7Dp7P%2FzN_%3Cb4E.A%5Dm,g%3Cj7P0SttAc%3ANu.d9U%7CB%5DpM08.%7DZnIa6%40_%3Bv2FpDLhawxEr-%5BuTpJZ%40-r%3Ec2Jh9e%3EN7%5Bo%3Ed6MhKlx%7D_sO%5C9rr%3Bo2RoN%7E5Fv%3D_.Pw4"
+}
+```
+### images
+  The visual representation of an entity usually in the form of a png, jpeg, gif, or svg file.
+* **Type:** ImageField
+* **Example:**
+```
+{
+	"images": [
+		{
+			"url": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FEvtt%3Ey%5D9LZ4_0M_JX%7E%3El%40PoEqzTzRm1.%7BGW",
+			"primary": true
+		},
+		{
+			"url": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0Stn8p.%5DjEp9G.Bd%7BkqXrSQgKx-h%2FYZ-Z8%5Dp-D%3B%7Cd-j%7DAQGVT%7Dp7P%2FzN_%3Cb4E.A%5Dm",
+			"primary": false
+		},
+		{
+			"url": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0SttAc%3ANu.d9U%7CB%5DpM08.%7DZnIa6%40_%3Bv2FpDLhawxEr-%5BuTpJZ%40-r%3Ec2Jh9e%3EN7%5Bo%3Ed6MhKlx%7D_sO%5C9rr%3Bo2RoN%7E5Fv%3D_.Pw4",
+			"primary": false
+		}
+	]
+}
+```
+### importance
+  A number between 0 and 100 indicating how important or popular an entity is.
+* **Type:** Float
+* **Example:**
+```
+{
+	"importance": 96.83421325683594
+}
+```
 ### instagramUri
   Link to the Instagram profile of the Person entity
 * **Type:** URL
@@ -798,24 +988,15 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"interests": [
 		{
-			"recordId": "EEIzhzuLVPeKuQ7KjPSa6aQ@329",
 			"name": "investing",
-			"surfaceForm": "investing",
-			"position": "personInterest",
 			"type": "Miscellaneous"
 		},
 		{
-			"recordId": "EEIzhzuLVPeKuQ7KjPSa6aQ@330",
 			"name": "planning",
-			"surfaceForm": "planning",
-			"position": "personInterest",
 			"type": "Miscellaneous"
 		},
 		{
-			"recordId": "EEIzhzuLVPeKuQ7KjPSa6aQ@331",
 			"name": "lobbying",
-			"surfaceForm": "lobbying",
-			"position": "personInterest",
 			"type": "Miscellaneous"
 		}
 	]
@@ -827,7 +1008,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"languages": []
+	"languages": {}
 }
 ```
 ### linkedInUri
@@ -836,7 +1017,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"linkedInUri": "linkedin.com/in/tom-wheeler-222878"
+	"linkedInUri": "linkedin.com/in/tom-wheeler-62255214"
 }
 ```
 ### location
@@ -847,75 +1028,74 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"location": {
 		"country": {
-			"summary": "Sovereign state in North America",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEQ%3El%601Nw%7BM0Bf7hu7z%3FRe9s4XwGXedrKUAN%28%3D%5ECHnM%60%29.%7BOV",
+			"summary": "Country located primarily in North America",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ",
 			"types": [
 				"Place",
-				"AdministrativeArea"
+				"AdministrativeArea",
+				"Country"
 			],
-			"name": "United States of America",
+			"name": "United States",
 			"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
-			"targetDiffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
 			"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
-			"type": "AdministrativeArea"
+			"type": "Place"
 		},
 		"isCurrent": true,
-		"address": "Washington, D.C.",
+		"address": "Washington, District of Columbia, USA",
 		"city": {
-			"summary": "Capital city of the United States",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FbvAT%3ExS%7DYb%3B%60zUb%3DXSAyK_oGyzSxB%3C1%5C6DR7P.Ar4",
+			"summary": "Capital city of the United States of America",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3Fav%40q%3EkZ%7DTb%3B%60z8%5BKaxFmK%5Ct%2Cd_.U.l8W",
 			"types": [
 				"Place",
-				"AdministrativeArea"
+				"AdministrativeArea",
+				"City"
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 			"name": "Washington, D.C.",
 			"diffbotUri": "http://diffbot.com/entity/Ep2MLLdkjO_C-R6NA7cOlcQ",
-			"targetDiffbotUri": "http://diffbot.com/entity/Ep2MLLdkjO_C-R6NA7cOlcQ",
 			"targetDiffbotId": "Ep2MLLdkjO_C-R6NA7cOlcQ",
-			"type": "AdministrativeArea"
+			"type": "Place"
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 		"metroArea": {
 			"summary": "Metropolitan area centered on Washington, D.C.",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FFvup%3EiQNof%3Bo9Uc%3Dl.Bv%3E",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FEvtp%3EzA%7B%3BdBsza%7DX2A%5E-m-8l7Sx-fyIOR%3Cb7Pq%7Dr6Hs9jw9%7CATg%3Dh%40N%7DSb8a18%3F%3F_%7C%3Dc%3DY.Fmz",
 			"types": [
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 			"name": "Washington metropolitan area",
 			"diffbotUri": "http://diffbot.com/entity/EbKIavbI8PhiHKmthsK_vTw",
-			"targetDiffbotUri": "http://diffbot.com/entity/EbKIavbI8PhiHKmthsK_vTw",
 			"targetDiffbotId": "EbKIavbI8PhiHKmthsK_vTw",
-			"type": "AdministrativeArea"
+			"type": "Place"
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-			"summary": "Capital city of the United States",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FbvAT%3ExS%7DYb%3B%60zUb%3DXSAyK_oGyzSxB%3C1%5C6DR7P.Ar4",
+			"summary": "Capital city of the United States of America",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3Fav%40q%3EkZ%7DTb%3B%60z8%5BKaxFmK%5Ct%2Cd_.U.l8W",
 			"types": [
 				"Place",
-				"AdministrativeArea"
+				"AdministrativeArea",
+				"City"
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 			"name": "Washington, D.C.",
 			"diffbotUri": "http://diffbot.com/entity/Ep2MLLdkjO_C-R6NA7cOlcQ",
-			"targetDiffbotUri": "http://diffbot.com/entity/Ep2MLLdkjO_C-R6NA7cOlcQ",
 			"targetDiffbotId": "Ep2MLLdkjO_C-R6NA7cOlcQ",
-			"type": "AdministrativeArea"
+			"type": "Place"
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 		"precision": 13.315855979919434,
 		"postalCode": "20032",
 		"surfaceForm": "Washington, District of Columbia, USA",
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+			"summary": "Capital city of the United States of America",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3Fav%40q%3EkZ%7DTb%3B%60z8%5BKaxFmK%5Ct%2Cd_.U.l8W",
 			"types": [
 				"Place",
-				"AdministrativeArea"
+				"AdministrativeArea",
+				"City"
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 			"name": "Washington, D.C.",
 			"diffbotUri": "http://diffbot.com/entity/Ep2MLLdkjO_C-R6NA7cOlcQ",
-			"targetDiffbotUri": "http://diffbot.com/entity/Ep2MLLdkjO_C-R6NA7cOlcQ",
 			"targetDiffbotId": "Ep2MLLdkjO_C-R6NA7cOlcQ",
-			"type": "AdministrativeArea"
+			"type": "Place"
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 		"longitude": -77.01712036132812
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@@ -930,215 +1110,232 @@ Note that certain longer field examples may be truncated for readability.
 	"locations": [
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+				"summary": "Country located primarily in North America",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ",
 				"types": [
 					"Place",
-					"AdministrativeArea"
+					"AdministrativeArea",
+					"Country"
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-				"name": "United States of America",
+				"name": "United States",
 				"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
-				"targetDiffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
 				"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
-				"type": "AdministrativeArea"
+				"type": "Place"
 			},
 			"isCurrent": true,
-			"address": "Washington, D.C.",
+			"address": "Washington, District of Columbia, USA",
 			"city": {
-				"summary": "Capital city of the United States",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FbvAT%3ExS%7DYb%3B%60zUb%3DXSAyK_oGyzSxB%3C1%5C6DR7P.Ar4",
+				"summary": "Capital city of the United States of America",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3Fav%40q%3EkZ%7DTb%3B%60z8%5BKaxFmK%5Ct%2Cd_.U.l8W",
 				"types": [
 					"Place",
-					"AdministrativeArea"
+					"AdministrativeArea",
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 				"targetDiffbotId": "Ep2MLLdkjO_C-R6NA7cOlcQ",
-				"type": "AdministrativeArea"
+				"type": "Place"
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 				"summary": "Metropolitan area centered on Washington, D.C.",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FFvup%3EiQNof%3Bo9Uc%3Dl.Bv%3E",
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 				"name": "Washington metropolitan area",
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 				"targetDiffbotId": "EbKIavbI8PhiHKmthsK_vTw",
-				"type": "AdministrativeArea"
+				"type": "Place"
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+				"summary": "Capital city of the United States of America",
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 				"types": [
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+					"AdministrativeArea",
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 				"targetDiffbotId": "Ep2MLLdkjO_C-R6NA7cOlcQ",
-				"type": "AdministrativeArea"
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+				"summary": "Capital city of the United States of America",
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 				"types": [
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 				"targetDiffbotId": "Ep2MLLdkjO_C-R6NA7cOlcQ",
-				"type": "AdministrativeArea"
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+				"summary": "Country located primarily in North America",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ",
 				"types": [
 					"Place",
-					"AdministrativeArea"
+					"AdministrativeArea",
+					"Country"
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-				"name": "United States of America",
+				"name": "United States",
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-				"targetDiffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
 				"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
-				"type": "AdministrativeArea"
+				"type": "Place"
 			},
-			"isCurrent": false,
-			"address": "Redlands, California",
+			"address": "409 Santa Monica Boulevard, Santa Monica, California",
 			"city": {
-				"summary": "City in San Bernardino County, California, United States",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FCvrv%3ExO%3ALE1l9Bl%3Cb%7DGej%5C%7BRyDCUDe%7BV0I%5E7Pdgj0RnJj3%3B%7C%3ESgGu1EiSd2U2Kb%3FchDc3D_NbtOi%7DVnTj%3DL9FE%2F%5B%7DG%5D9%5B%7D7d.ZvE",
+				"summary": "Beachfront city in Los Angeles County, California, United States",
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+				"types": [
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+					"AdministrativeArea",
+					"City"
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+				"name": "Santa Monica",
+				"diffbotUri": "http://diffbot.com/entity/EHwsBJbg3M7exvBfQN-WJ8Q",
+				"targetDiffbotId": "EHwsBJbg3M7exvBfQN-WJ8Q",
+				"type": "Place"
+			},
+			"street": "409 Santa Monica Boulevard",
+			"metroArea": {
+				"summary": "Metropolitan area in California, United States",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FEvtu%3Eq%5D%3FLD%3Aa0M_K%2CnkG6SxSrzXzHXsY3.Z%3EV",
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-				"diffbotUri": "http://diffbot.com/entity/EEGqoBftsOZyh3_RKbQE3mw",
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-				"targetDiffbotId": "EEGqoBftsOZyh3_RKbQE3mw",
-				"type": "AdministrativeArea"
+				"name": "Los Angeles metropolitan area",
+				"diffbotUri": "http://diffbot.com/entity/EKhZFGU1RPQi0GJOv2ZIylw",
+				"targetDiffbotId": "EKhZFGU1RPQi0GJOv2ZIylw",
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 				"summary": "County in California, United States",
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 				"types": [
 					"Place",
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-				"name": "San Bernardino County",
-				"diffbotUri": "http://diffbot.com/entity/EApueG2dHP3iRBLbjF2w2gQ",
-				"targetDiffbotUri": "http://diffbot.com/entity/EApueG2dHP3iRBLbjF2w2gQ",
-				"targetDiffbotId": "EApueG2dHP3iRBLbjF2w2gQ",
-				"type": "AdministrativeArea"
+				"name": "Los Angeles County",
+				"diffbotUri": "http://diffbot.com/entity/ELvekhrK-MZSKBlAHI-t_Pg",
+				"targetDiffbotId": "ELvekhrK-MZSKBlAHI-t_Pg",
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-			"latitude": 34.04679489135742,
-			"precision": 9.702208518981934,
-			"postalCode": "92374",
-			"surfaceForm": "Redlands, California",
+			"latitude": 34.0155143737793,
+			"precision": 0.22360679507255554,
+			"postalCode": "90401",
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 				"types": [
 					"Place",
-					"AdministrativeArea"
+					"AdministrativeArea",
+					"Region"
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 				"name": "California",
 				"diffbotUri": "http://diffbot.com/entity/El0_8ehooNxOPT36Y4RdV9w",
-				"targetDiffbotUri": "http://diffbot.com/entity/El0_8ehooNxOPT36Y4RdV9w",
 				"targetDiffbotId": "El0_8ehooNxOPT36Y4RdV9w",
-				"type": "AdministrativeArea"
+				"type": "Place"
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-			"longitude": -117.17427062988281
+			"longitude": -118.4967041015625
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 		{
 			"country": {
-				"summary": "Sovereign state in North America",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEQ%3El%601Nw%7BM0Bf7hu7z%3FRe9s4XwGXedrKUAN%28%3D%5ECHnM%60%29.%7BOV",
+				"summary": "Country located primarily in North America",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ",
 				"types": [
 					"Place",
-					"AdministrativeArea"
+					"AdministrativeArea",
+					"Country"
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-				"name": "United States of America",
+				"name": "United States",
 				"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
-				"targetDiffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
 				"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
-				"type": "AdministrativeArea"
+				"type": "Place"
 			},
-			"isCurrent": false,
-			"address": "Cambridge, Massachusetts",
+			"address": "Boston, Massachusetts",
 			"city": {
-				"summary": "City in Middlesex County, Massachusetts, United States",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3Fav%40s%3EhO9Ou5%5E2FYEZn%40o%3EUrMl3X.Sgy",
+				"summary": "Capital and largest city of Massachusetts, United States",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FBvqP%3Exc2Sr8eztiMg3QetNyWf%7EL7V%5E6d46Y%3CRt%40l%3CU%5DN%60u9iGSg%5Bu6TwTm4a5%3Af5Uf1p4Fq%3B%3F2O%7EJ_iPr6P2Pd%7Ehz%3F.Eip",
 				"types": [
 					"Place",
-					"AdministrativeArea"
+					"AdministrativeArea",
+					"City"
 				],
-				"name": "Cambridge",
-				"diffbotUri": "http://diffbot.com/entity/EKtEQ-seQOfuiSDMTnvM9tA",
-				"targetDiffbotUri": "http://diffbot.com/entity/EKtEQ-seQOfuiSDMTnvM9tA",
-				"targetDiffbotId": "EKtEQ-seQOfuiSDMTnvM9tA",
-				"type": "AdministrativeArea"
+				"name": "Boston",
+				"diffbotUri": "http://diffbot.com/entity/E7vnJ0j-OP4qXP4s9wNDbEQ",
+				"targetDiffbotId": "E7vnJ0j-OP4qXP4s9wNDbEQ",
+				"type": "Place"
 			},
 			"metroArea": {
 				"summary": "Metropolitan area in Massachusetts, New Hampshire and Rhode Island, USA",
 				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FEvtp%3El%601Nw1l%7DPmLh%7DZ.G%5Bm",
 				"types": [
-					"Place"
+					"Place",
+					"AdministrativeArea"
 				],
 				"name": "Greater Boston",
 				"diffbotUri": "http://diffbot.com/entity/Es5VXYfClMLeSpzD5N0Cx1A",
-				"targetDiffbotUri": "http://diffbot.com/entity/Es5VXYfClMLeSpzD5N0Cx1A",
 				"targetDiffbotId": "Es5VXYfClMLeSpzD5N0Cx1A",
 				"type": "Place"
 			},
 			"subregion": {
 				"summary": "County in Massachusetts, United States",
-				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FcvBQ%3ErO%3CLr2YhBmKZr%40%7BJRzXxzL%7BJa%7EYx%3Fd7%5Dl%7DI6G%60F%604%3F082w%5BuA_.Xq%7B",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEv%3ExS%7DYb%3B%60z4o%3E_%7EDq60uYs%3F%5D%2CBFsc48S6dx3pAV.Jix",
 				"types": [
 					"Place",
-					"AdministrativeArea"
+					"AdministrativeArea",
+					"Subregion"
 				],
-				"name": "Middlesex County",
-				"diffbotUri": "http://diffbot.com/entity/EfTXOkq9_P2GytZP4wTfK1g",
-				"targetDiffbotUri": "http://diffbot.com/entity/EfTXOkq9_P2GytZP4wTfK1g",
-				"targetDiffbotId": "EfTXOkq9_P2GytZP4wTfK1g",
-				"type": "AdministrativeArea"
+				"name": "Suffolk County",
+				"diffbotUri": "http://diffbot.com/entity/EIFKVGfbmM5-wj_KE0Yx4oQ",
+				"targetDiffbotId": "EIFKVGfbmM5-wj_KE0Yx4oQ",
+				"type": "Place"
 			},
-			"latitude": 42.3803596496582,
-			"precision": 4.150406360626221,
-			"postalCode": "02138",
-			"surfaceForm": "Cambridge, Massachusetts",
+			"latitude": 42.355491638183594,
+			"precision": 11.640422821044922,
+			"postalCode": "02110",
 			"region": {
 				"summary": "State of the United States of America",
 				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FivHp%3ExS%7DYb%3B%60z%7E%5BKlp%3BnL%60kXy%3E.5Y%60",
 				"types": [
 					"Place",
-					"AdministrativeArea"
+					"AdministrativeArea",
+					"Region"
 				],
 				"name": "Massachusetts",
 				"diffbotUri": "http://diffbot.com/entity/E0VAbhEeRNsSvhHIpmhd3Xw",
-				"targetDiffbotUri": "http://diffbot.com/entity/E0VAbhEeRNsSvhHIpmhd3Xw",
 				"targetDiffbotId": "E0VAbhEeRNsSvhHIpmhd3Xw",
-				"type": "AdministrativeArea"
+				"type": "Place"
 			},
-			"longitude": -71.1159896850586
+			"longitude": -71.04861450195312
 		}
 	]
 }
 ```
+### name
+  Primary text label for this entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"name": "Tom Wheeler"
+}
+```
 ### nameDetail
   Parts of the name (e.g., first name, last name, middle name).
 * **Type:** NameDetail
@@ -1146,8 +1343,14 @@ Note that certain longer field examples may be truncated for readability.
 ```
 {
 	"nameDetail": {
-		"firstName": "Tom",
-		"lastName": "Wheeler"
+		"firstName": "Thomas",
+		"lastName": "Wheeler",
+		"middleName": [
+			"Edgar"
+		],
+		"nicknames": [
+			"Tom"
+		]
 	}
 }
 ```
@@ -1159,17 +1362,39 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"nationalities": [
 		{
-			"recordId": "EEIzhzuLVPeKuQ7KjPSa6aQ@336",
-			"name": "United States of America",
-			"websiteUris": [
-				"wikidata.org/entity/Q30"
-			],
-			"position": "nationalities",
+			"name": "United States",
 			"type": "AdministrativeArea"
 		}
 	]
 }
 ```
+### nbFollowers
+  The sum of followers across social networks
+* **Type:** Integer
+* **Example:**
+```
+{
+	"nbFollowers": 14008
+}
+```
+### nbIncomingEdges
+  This is the number of edges in the Knowledge Graph that point to this entity. For example, the nbIncomingEdges field for Google is over 100,000. This number includes the number of people that work at google, the number of investors who invested in google, etc.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"nbIncomingEdges": 31
+}
+```
+### nbOrigins
+  Total number of origins in the field &#39;origins&#39;. This field is only available in extended JSON mode.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"nbOrigins": 69
+}
+```
 ### netWorth
   A person&#39;s estimated net worth (the value the assets minus liabilities).
 * **Type:** Amount
@@ -1177,11 +1402,60 @@ Note that certain longer field examples may be truncated for readability.
 ```
 {
 	"netWorth": {
-		"currency": "",
-		"value": ""
+		"currency": "USD",
+		"value": 9663373
 	}
 }
 ```
+### nonCanonicalFacts
+  Enumerates all the non-canonical fields (i.e., those not defined in the ontology) that have a value for this entity. For instance, if &#39;numberOfChildren&#39; is listed in &#39;nonCanonicalFacts&#39; then the entity JSON will have the key &#39;numberOfChildren&#39; with an associated value. This field is only provided when the parameter nonCanonicalFacts&#x3D;1 is set. See: https:&#x2F;&#x2F;docs.diffbot.com&#x2F;kgapi
+* **Type:** String
+* **Example:**
+```
+{
+	"nonCanonicalFacts": ""
+}
+```
+### npiNumbers
+  The National Provider Identifier (NPI) is a unique identification number for covered health care providers. 
+* **Type:** String
+* **Example:**
+```
+{
+	"npiNumbers": ""
+}
+```
+### originDetails
+  Additional information about origins listed in &#39;origins&#39;, including the latest time it was crawled. This field is only available in extended JSON mode.
+* **Type:** OriginDetail
+* **Example:**
+```
+{
+	"originDetails": [
+		{
+			"crawledAt": {
+				"str": "",
+				"precision": 0,
+				"timestamp": 0
+			},
+			"origin": ""
+		}
+	]
+}
+```
+### origins
+  An origin is a web address where Diffbot found one or more facts about an entity. This field is only available in extended JSON mode.
+* **Type:** String
+* **Example:**
+```
+{
+	"origins": [
+		"abcnews.go.com/Technology/wireStory/apple-aims-solve-problems-locating-911-calls-55969895",
+		"asianage.com/technology/in-other-news/180618/apple-aims-to-solve-problems-locating-911-calls-for-help.html",
+		"bloomberg.com/profile/person/2045213"
+	]
+}
+```
 ### parents
   This person&#39;s parents.
 * **Type:** LinkedEntity
@@ -1202,11 +1476,8 @@ Note that certain longer field examples may be truncated for readability.
 				}
 			],
 			"types": "",
-			"websiteUris": "",
 			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
+			"name": ""
 		}
 	]
 }
@@ -1233,54 +1504,28 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"politicalAffiliation": [
 		{
-			"recordId": "EEIzhzuLVPeKuQ7KjPSa6aQ@337",
 			"name": "Democratic Party",
-			"websiteUris": [
-				"wikidata.org/entity/Q29552"
-			],
-			"surfaceForm": "Democratic Party",
-			"position": "politicalAffiliation",
 			"type": "Organization"
 		}
 	]
 }
 ```
-### posts
-  Posts written by this person.
-* **Type:** LinkedEntity
+### religion
+  This person&#39;s religion.
+* **Type:** Religion
 * **Example:**
 ```
 {
-	"posts": [
-		{
-			"summary": "",
-			"image": "",
-			"images": [
-				{
-					"classifications": "",
-					"fingerprint": "",
-					"title": "",
-					"isCached": false,
-					"url": ""
-				}
-			],
-			"types": "",
-			"websiteUris": "",
-			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
-		}
-	]
+	"religion": {}
 }
 ```
-### religion
-  This person&#39;s religion.
-* **Type:** Religion
+### sepMexicoIds
+  The identification number of the profession license provided by Secretaría de Educación Pública (SEP).
+* **Type:** String
 * **Example:**
 ```
 {
-	"religion": ""
+	"sepMexicoIds": ""
 }
 ```
 ### siblings
@@ -1303,11 +1548,8 @@ Note that certain longer field examples may be truncated for readability.
 				}
 			],
 			"types": "",
-			"websiteUris": "",
 			"diffbotUri": "",
-			"name": "",
-			"targetDiffbotUri": "",
-			"surfaceForm": ""
+			"name": ""
 		}
 	]
 }
@@ -1322,34 +1564,58 @@ Note that certain longer field examples may be truncated for readability.
 		{
 			"name": "investment",
 			"diffbotUri": "http://diffbot.com/entity/Emyrk4p-WOvGnIkgRO_yaGA",
-			"targetDiffbotUri": "http://diffbot.com/entity/Emyrk4p-WOvGnIkgRO_yaGA",
-			"targetDiffbotId": "Emyrk4p-WOvGnIkgRO_yaGA",
-			"surfaceForm": "investment"
+			"targetDiffbotId": "Emyrk4p-WOvGnIkgRO_yaGA"
 		},
 		{
 			"name": "economics",
-			"diffbotUri": "http://diffbot.com/entity/EoQMvZcJoP42rI4Eo0Avfdg",
-			"targetDiffbotUri": "http://diffbot.com/entity/EoQMvZcJoP42rI4Eo0Avfdg",
-			"targetDiffbotId": "EoQMvZcJoP42rI4Eo0Avfdg",
-			"surfaceForm": "economics"
+			"diffbotUri": "http://diffbot.com/entity/E9kGv6JTWPMyWBAvoCfaQuw",
+			"targetDiffbotId": "E9kGv6JTWPMyWBAvoCfaQuw"
 		},
 		{
 			"name": "teaching",
 			"diffbotUri": "http://diffbot.com/entity/Ez8ugmNmEN3mp_4eMLqGSsA",
-			"targetDiffbotUri": "http://diffbot.com/entity/Ez8ugmNmEN3mp_4eMLqGSsA",
-			"targetDiffbotId": "Ez8ugmNmEN3mp_4eMLqGSsA",
-			"surfaceForm": "teaching"
+			"targetDiffbotId": "Ez8ugmNmEN3mp_4eMLqGSsA"
 		}
 	]
 }
 ```
+### summary
+  A short phrase designed to disambiguate entities with the same or similar name
+* **Type:** String
+* **Example:**
+```
+{
+	"summary": "American businessman and politician"
+}
+```
 ### twitterUri
   Link to the Twitter profile of the Person entity
 * **Type:** URL
 * **Example:**
 ```
 {
-	"twitterUri": "twitter.com/TomWheelerFCC"
+	"twitterUri": "twitter.com/tomwheelerfcc"
+}
+```
+### type
+  The top-level type of a Diffbot entity. Examples of type include Person, Organization, Article, Product.
+* **Type:** Type
+* **Example:**
+```
+{
+	"type": "Person"
+}
+```
+### types
+  All types of a Diffbot entity, including the value of the field &#39;type&#39;.
+* **Type:** String
+* **Example:**
+```
+{
+	"types": [
+		"Person",
+		"PersonInvestor"
+	]
 }
 ```
 ### unions
@@ -1374,11 +1640,8 @@ Note that certain longer field examples may be truncated for readability.
 					}
 				],
 				"types": "",
-				"websiteUris": "",
 				"diffbotUri": "",
-				"name": "",
-				"targetDiffbotUri": "",
-				"surfaceForm": ""
+				"name": ""
 			},
 			"from": {
 				"str": "",
@@ -1404,6 +1667,60 @@ Note that certain longer field examples may be truncated for readability.
 	"weight": ""
 }
 ```
+### wikipediaPageviews
+  The number of views of its Wikipedia page of the last month if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviews": 1165
+}
+```
+### wikipediaPageviewsGrowth
+  The month over month growth of wikipediaPageviews, where we count the increment of the number of page views of the second to last (full) month, compared with that of the last (full) month. if today was Aug 16th, 2022, the last complete month is July. So it refers to the increment from June to July, i.e., ( f(July) - f(June) ) ÷ f(June) x 100%. The f(.) only counts the first 28 days of a month, to avoid fluctuations between 31-days months like Jan and 28(29)-days months like Feb.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsGrowth": 0.13216715
+}
+```
+### wikipediaPageviewsLastQuarter
+  The number of views of its Wikipedia page of the last quarter if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastQuarter": 4654
+}
+```
+### wikipediaPageviewsLastQuarterGrowth
+  The quarter over quarter growth of wikipediaPageviews, where we count the increment of the number of page views of the second to last (full) quarter, compared with that of the last (full) quarter. If today was Aug 16th, 2022, the last complete quarter is Q2 (April, May, June). So it refers to the increment from Q1 to Q2, i.e., ( f(Q2) - f(Q1) ) ÷ f(Q1) x 100%.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastQuarterGrowth": 0.8698272
+}
+```
+### wikipediaPageviewsLastYear
+  The number of views of its Wikipedia page of the last year if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastYear": 10562
+}
+```
+### wikipediaPageviewsLastYearGrowth
+  The year over year growth of wikipediaPageviews, where we count the monthly-rolling increment of the year before last than the last year. It today was Aug 16th, 2022, it is computed by comparing the numbers from Aug 2021 to July 2022 and from Aug 2020 to July 2021, i.e., ( f(Aug 2021 to July 2022) - f(Aug 2020 to July 2021) ) ÷ f(Aug 2020 to July 2021) x 100%.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastYearGrowth": -0.054685403
+}
+```
 ### wikipediaUri
   Link to the Wikipedia page of the Person entity
 * **Type:** URL
diff --git a/docs/kg-ont-place.md b/docs/kg-ont-place.md
index 2e1ab449..ffbedfe8 100644
--- a/docs/kg-ont-place.md
+++ b/docs/kg-ont-place.md
@@ -1,22 +1,354 @@
 ---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
 id: kg-ont-place
 title: Place
+generatedBy: generateOntology.js
 ---
 
 The place entity type encompasses cities, landmarks, countries, administrative areas, and other locations known to the Knowledge Graph. 
 
 Note that fields are not guaranteed to exist in every entity record.
 
->New to the Diffbot Knowledge Graph? [Start here](dql-quickstart).
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
 
 ## Place Fields
+* [allDescriptions](#alldescriptions) 
+* [allNames](#allnames) 
+* [allOriginHashes](#alloriginhashes) 
+* [allUriDetails](#alluridetails) 
+* [allUris](#alluris) 
+* [area](#area) 
+* [areaCodes](#areacodes) 
+* [crawlTimestamp](#crawltimestamp) 
+* [description](#description) 
+* [descriptors](#descriptors) 
+* [diffbotUri](#diffboturi) 
+* [headOfPlace](#headofplace) 
+* [id](#id) 
+* [image](#image) 
+* [images](#images) 
+* [importance](#importance) 
 * [isPartOf](#ispartof) 
 * [location](#location) 
+* [name](#name) 
+* [nbIncomingEdges](#nbincomingedges) 
+* [nbOrigins](#nborigins) 
+* [nonCanonicalFacts](#noncanonicalfacts) 
+* [originDetails](#origindetails) 
+* [origins](#origins) 
 * [placeType](#placetype) 
+* [population](#population) 
+* [postalCodes](#postalcodes) 
+* [summary](#summary) 
+* [type](#type) 
+* [types](#types) 
+* [wikipediaPageviews](#wikipediapageviews) 
+* [wikipediaPageviewsGrowth](#wikipediapageviewsgrowth) 
+* [wikipediaPageviewsLastQuarter](#wikipediapageviewslastquarter) 
+* [wikipediaPageviewsLastQuarterGrowth](#wikipediapageviewslastquartergrowth) 
+* [wikipediaPageviewsLastYear](#wikipediapageviewslastyear) 
+* [wikipediaPageviewsLastYearGrowth](#wikipediapageviewslastyeargrowth) 
 
 ## Place Field Details
 Note that certain longer field examples may be truncated for readability.
 
+### allDescriptions
+  All descriptions found for this entity. For the best description, refer to the field &#39;description&#39;.
+* **Type:** String
+* **Example:**
+```
+{
+	"allDescriptions": [
+		"Country located primarily in North America",
+		"The United States of America (USA), also known as the United States (U.S) or America, is a country primarily located in North America. It is a federal republic of 50 states and a federal capital district, Washington, D.C. The 48 contiguous states border Canada to the north and Mexico to the south, with the semi-exclave of Alaska in the northwest and the archipelago of Hawaii in the Pacific Ocean. The United States also asserts sovereignty over five major island territories and various uninhabited islands in Oceania and the Caribbean. It is a megadiverse country, with the world's third-largest land area and third-largest population, exceeding 340 million."
+	]
+}
+```
+### allNames
+  All names used, including nicknames, full names and transliterations to other languages.
+* **Type:** String
+* **Example:**
+```
+{
+	"allNames": [
+		"Vereenichde Staate van Amerika",
+		"Stados Ounidos de la América",
+		"د امریکا متحده ایالات"
+	]
+}
+```
+### allOriginHashes
+  For Diffbot&#39;s internal use only.
+* **Type:** String
+* **Example:**
+```
+{
+	"allOriginHashes": [
+		"XM-p70f3OhaqLnsuKWeABA",
+		"oITpNcvcM2GYrb07pvWDaQ",
+		"j-tkJEFSNsGfGsJlEGDLNA"
+	]
+}
+```
+### allUriDetails
+  Additional information about each URI in &#39;allUris&#39;, which lists the URIs associated with this entity.
+* **Type:** UriDetails
+* **Example:**
+```
+{
+	"allUriDetails": [
+		{
+			"domainMonthlyTrafficGrowth": "",
+			"domainMonthlyTraffic": 0,
+			"redirectsTo": "",
+			"nbFollowing": 0,
+			"uriType": "",
+			"verified": false,
+			"nbLinkedAccounts": 0,
+			"nbFollowers": 0,
+			"httpCodeTimestamp": 0,
+			"httpCode": "",
+			"uri": ""
+		}
+	]
+}
+```
+### allUris
+  All URIs associated with an entity. A URI (uniform resource identifier) is a page on the web that describes an entity (e.g., an company&#39;s homepage or a person&#39;s social network profile).
+* **Type:** URL
+* **Example:**
+```
+{
+	"allUris": [
+		"wikidata.org/entity/Q30",
+		"en.wikipedia.org/?curid=3434750",
+		"en.wikipedia.org/wiki/United_States"
+	]
+}
+```
+### area
+  Square kilometers of AdministrativeArea
+* **Type:** Integer
+* **Example:**
+```
+{
+	"area": 9826675
+}
+```
+### areaCodes
+  
+* **Type:** String
+* **Example:**
+```
+{
+	"areaCodes": ""
+}
+```
+### crawlTimestamp
+  The default crawlTimestamp is the most recent date of all of the crawlTimestamps of the origins used to compute the Entity, returned as a UNIX time.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"crawlTimestamp": 1756105200
+}
+```
+### description
+  A few sentences describing an entity
+* **Type:** String
+* **Example:**
+```
+{
+	"description": "The United States of America (USA), also known as the United States (U.S) or America, is a country primarily located in North America. It is a federal republic of 50 states and a federal capital district, Washington, D.C. The 48 contiguous states border Canada to the north and Mexico to the south, with the semi-exclave of Alaska in the northwest and the archipelago of Hawaii in the Pacific Ocean. The United States also asserts sovereignty over five major island territories and various uninhabited islands in Oceania and the Caribbean. It is a megadiverse country, with the world's third-largest land area and third-largest population, exceeding 340 million."
+}
+```
+### descriptors
+  A list of free-form keywords describing this entity
+* **Type:** String
+* **Example:**
+```
+{
+	"descriptors": ""
+}
+```
+### diffbotUri
+  diffbotUri is the URI an entity&#39;s  (URI), which is defined by appending the Diffbot ID to the URL https:&#x2F;&#x2F;diffbot.com&#x2F;entity&#x2F;. For example, Diffbot&#39;s entityID is CWSwJ_SWQPfqO3HQsxY4lGg and its DiffbotUri is https:&#x2F;&#x2F;diffbot.com&#x2F;entity&#x2F;CWSwJ_SWQPfqO3HQsxY4lGg
+* **Type:** URL
+* **Example:**
+```
+{
+	"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A"
+}
+```
+### headOfPlace
+  Leaders of this place, including head of government and head of state.
+* **Type:** HeadOfPlace
+* **Example:**
+```
+{
+	"headOfPlace": [
+		{
+			"isCurrent": false,
+			"headOfPlace": {
+				"summary": "46th President of the United States",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7guSXzAoBWu.x0KwLZrUn.%5B%3CR0Aa4Hwygr9m6W%3Exl5G%60BkxmYDS%7B%2Fl0_9%40jJ%5E2Aj%3C%5BzMf7C2Rk6br%40d.Yu5",
+				"types": [
+					"Person"
+				],
+				"name": "Joe Biden",
+				"diffbotUri": "http://diffbot.com/entity/E4TlFcudMNuaX0eYAWet-8w",
+				"targetDiffbotId": "E4TlFcudMNuaX0eYAWet-8w",
+				"type": "Person"
+			},
+			"from": {
+				"str": "d2021-01-20",
+				"precision": 3,
+				"timestamp": 1611100800000
+			},
+			"to": {
+				"str": "d2025-01-20",
+				"precision": 3,
+				"timestamp": 1737331200000
+			},
+			"title": "President of the United States",
+			"category": {
+				"types": [
+					"Intangible",
+					"EmploymentCategory"
+				],
+				"name": "Head of government",
+				"diffbotUri": "http://diffbot.com/entity/EG9NYFQwRNZKIOLTW5WwHcw",
+				"targetDiffbotId": "EG9NYFQwRNZKIOLTW5WwHcw",
+				"type": "EmploymentCategory"
+			}
+		},
+		{
+			"isCurrent": false,
+			"headOfPlace": {
+				"summary": "First Lady of the United States from 2001 to 2009",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7guSXzAoBWu.x0KwLZrUn.%5B%3CR0Aa4Hwygr9m6W%3Exl5G%60BkxmQ6%60%7ENu%7DY%5DVm%40%2Cnxn%40YgRy3V1SrqC6D%5D7cdP%7CNi%5B%28%7E9%5Ei%29.rVn",
+				"types": [
+					"Person"
+				],
+				"name": "George Bush",
+				"diffbotUri": "http://diffbot.com/entity/EyXOt9wRKM3Okxt9ckzJpmg",
+				"targetDiffbotId": "EyXOt9wRKM3Okxt9ckzJpmg",
+				"type": "Person"
+			},
+			"from": {
+				"str": "d2001-01-20",
+				"precision": 3,
+				"timestamp": 979948800000
+			},
+			"to": {
+				"str": "d2009-01-20",
+				"precision": 3,
+				"timestamp": 1232409600000
+			},
+			"title": "President of the United States",
+			"category": {
+				"types": [
+					"Intangible",
+					"EmploymentCategory"
+				],
+				"name": "Head of government",
+				"diffbotUri": "http://diffbot.com/entity/EG9NYFQwRNZKIOLTW5WwHcw",
+				"targetDiffbotId": "EG9NYFQwRNZKIOLTW5WwHcw",
+				"type": "EmploymentCategory"
+			}
+		},
+		{
+			"isCurrent": false,
+			"headOfPlace": {
+				"summary": "President of the United States from 1993 to 2001",
+				"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7guSXzAoBWu.x0KwLZrUn.%5B%3CR0Aa4Hwygr9m6W%3Exl5G%60BkxmQ%3EZ8LF8c9UiF.yHm",
+				"types": [
+					"Person"
+				],
+				"name": "Bill Clinton",
+				"diffbotUri": "http://diffbot.com/entity/EVNcTf-3LNBKLsCg506B2pQ",
+				"targetDiffbotId": "EVNcTf-3LNBKLsCg506B2pQ",
+				"type": "Person"
+			},
+			"from": {
+				"str": "d1993-01-20",
+				"precision": 3,
+				"timestamp": 727488000000
+			},
+			"to": {
+				"str": "d2001-01-20",
+				"precision": 3,
+				"timestamp": 979948800000
+			},
+			"title": "President of the United States",
+			"category": {
+				"types": [
+					"Intangible",
+					"EmploymentCategory"
+				],
+				"name": "Head of government",
+				"diffbotUri": "http://diffbot.com/entity/EG9NYFQwRNZKIOLTW5WwHcw",
+				"targetDiffbotId": "EG9NYFQwRNZKIOLTW5WwHcw",
+				"type": "EmploymentCategory"
+			}
+		}
+	]
+}
+```
+### id
+  An alphanumeric string like CWSwJ_SWQPfqO3HQsxY4lGg that uniquely identifies an entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"id": "E01d4EK33MmCosgI2KXa4-A"
+}
+```
+### image
+  The main image used to represent the entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"image": "https://kg.diffbot.com/image/api/get?fetch=yes&urls=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ,g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FevDs%3El%601Nw%7BM0Bf7hu7z%3FRe9s4XwGXedrKUAN%28%40aCHnM%60%29.%7BOV,g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FgvFw%3Eq%5D%2FNw5i96Mi.2Nm"
+}
+```
+### images
+  The visual representation of an entity usually in the form of a png, jpeg, gif, or svg file.
+* **Type:** ImageField
+* **Example:**
+```
+{
+	"images": [
+		{
+			"url": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ",
+			"primary": false
+		},
+		{
+			"url": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FevDs%3El%601Nw%7BM0Bf7hu7z%3FRe9s4XwGXedrKUAN%28%40aCHnM%60%29.%7BOV",
+			"primary": false
+		},
+		{
+			"url": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FgvFw%3Eq%5D%2FNw5i96Mi.2Nm",
+			"primary": false
+		}
+	]
+}
+```
+### importance
+  A number between 0 and 100 indicating how important or popular an entity is.
+* **Type:** Float
+* **Example:**
+```
+{
+	"importance": 99.97929382324219
+}
+```
 ### isPartOf
   
 * **Type:** LinkedEntity
@@ -25,17 +357,20 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"isPartOf": [
 		{
-			"summary": "Sovereign state in North America",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEQ%3El%601Nw%7BM0Bf7hu7z%3FRe9s4XwGXedrKUAN%28%3D%5ECHnM%60%29.%7BOV",
-			"types": [
-				"Place",
-				"AdministrativeArea"
+			"summary": "",
+			"image": "",
+			"images": [
+				{
+					"classifications": "",
+					"fingerprint": "",
+					"title": "",
+					"isCached": false,
+					"url": ""
+				}
 			],
-			"name": "United States of America",
-			"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
-			"targetDiffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
-			"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
-			"type": "AdministrativeArea"
+			"types": "",
+			"diffbotUri": "",
+			"name": ""
 		}
 	]
 }
@@ -48,32 +383,202 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"location": {
 		"country": {
-			"summary": "Sovereign state in North America",
-			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FfvEQ%3El%601Nw%7BM0Bf7hu7z%3FRe9s4XwGXedrKUAN%28%3D%5ECHnM%60%29.%7BOV",
+			"summary": "Country located primarily in North America",
+			"image": "https://kg.diffbot.com/image/api/get?fetch=yes&url=g%3Cj7P0St0DnBJf.x0KwLZrUn.%5B%3CR0Aa4Hh%3B%5Bv738ZqOr7U%3FhvGq%3Eh%5D%7Dab%3B%60zBlElnGl6anIdpR%7BW%5EvOdKQBTx.oCJ",
 			"types": [
 				"Place",
-				"AdministrativeArea"
+				"AdministrativeArea",
+				"Country"
 			],
-			"name": "United States of America",
+			"name": "United States",
 			"diffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
-			"targetDiffbotUri": "http://diffbot.com/entity/E01d4EK33MmCosgI2KXa4-A",
 			"targetDiffbotId": "E01d4EK33MmCosgI2KXa4-A",
-			"type": "AdministrativeArea"
+			"type": "Place"
 		},
-		"isCurrent": false,
-		"address": "United States of America",
+		"address": "United States",
 		"latitude": 39.82817459106445,
 		"precision": 3134.752685546875,
+		"surfaceForm": "United States",
 		"longitude": -98.57949829101562
 	}
 }
 ```
+### name
+  Primary text label for this entity.
+* **Type:** String
+* **Example:**
+```
+{
+	"name": "United States"
+}
+```
+### nbIncomingEdges
+  This is the number of edges in the Knowledge Graph that point to this entity. For example, the nbIncomingEdges field for Google is over 100,000. This number includes the number of people that work at google, the number of investors who invested in google, etc.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"nbIncomingEdges": 1498200387
+}
+```
+### nbOrigins
+  Total number of origins in the field &#39;origins&#39;. This field is only available in extended JSON mode.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"nbOrigins": 9
+}
+```
+### nonCanonicalFacts
+  Enumerates all the non-canonical fields (i.e., those not defined in the ontology) that have a value for this entity. For instance, if &#39;numberOfChildren&#39; is listed in &#39;nonCanonicalFacts&#39; then the entity JSON will have the key &#39;numberOfChildren&#39; with an associated value. This field is only provided when the parameter nonCanonicalFacts&#x3D;1 is set. See: https:&#x2F;&#x2F;docs.diffbot.com&#x2F;kgapi
+* **Type:** String
+* **Example:**
+```
+{
+	"nonCanonicalFacts": ""
+}
+```
+### originDetails
+  Additional information about origins listed in &#39;origins&#39;, including the latest time it was crawled. This field is only available in extended JSON mode.
+* **Type:** OriginDetail
+* **Example:**
+```
+{
+	"originDetails": [
+		{
+			"crawledAt": {
+				"str": "",
+				"precision": 0,
+				"timestamp": 0
+			},
+			"origin": ""
+		}
+	]
+}
+```
+### origins
+  An origin is a web address where Diffbot found one or more facts about an entity. This field is only available in extended JSON mode.
+* **Type:** String
+* **Example:**
+```
+{
+	"origins": [
+		"dbpedia.org/page/United_States",
+		"en.wikipedia.org/?curid=3434750",
+		"en.wikipedia.org/wiki/United_States"
+	]
+}
+```
 ### placeType
-  Place category for a location; ex. Park, City, etc.
-* **Type:** PlaceType
+**`Deprecated`**  Deprecated: Used to denote Place category for a location; ex. Park, City, etc. &#x60;types&#x60; is now the preferred field for getting this information.
+* **Type:** String
 * **Example:**
 ```
 {
 	"placeType": "COUNTRY"
 }
 ```
+### population
+  
+* **Type:** Integer
+* **Example:**
+```
+{
+	"population": 340110988
+}
+```
+### postalCodes
+  
+* **Type:** String
+* **Example:**
+```
+{
+	"postalCodes": ""
+}
+```
+### summary
+  A short phrase designed to disambiguate entities with the same or similar name
+* **Type:** String
+* **Example:**
+```
+{
+	"summary": "Country located primarily in North America"
+}
+```
+### type
+  The top-level type of a Diffbot entity. Examples of type include Person, Organization, Article, Product.
+* **Type:** Type
+* **Example:**
+```
+{
+	"type": "Place"
+}
+```
+### types
+  All types of a Diffbot entity, including the value of the field &#39;type&#39;.
+* **Type:** String
+* **Example:**
+```
+{
+	"types": [
+		"Place",
+		"AdministrativeArea",
+		"Country"
+	]
+}
+```
+### wikipediaPageviews
+  The number of views of its Wikipedia page of the last month if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviews": 3049675
+}
+```
+### wikipediaPageviewsGrowth
+  The month over month growth of wikipediaPageviews, where we count the increment of the number of page views of the second to last (full) month, compared with that of the last (full) month. if today was Aug 16th, 2022, the last complete month is July. So it refers to the increment from June to July, i.e., ( f(July) - f(June) ) ÷ f(June) x 100%. The f(.) only counts the first 28 days of a month, to avoid fluctuations between 31-days months like Jan and 28(29)-days months like Feb.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsGrowth": -0.2279763
+}
+```
+### wikipediaPageviewsLastQuarter
+  The number of views of its Wikipedia page of the last quarter if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastQuarter": 9211423
+}
+```
+### wikipediaPageviewsLastQuarterGrowth
+  The quarter over quarter growth of wikipediaPageviews, where we count the increment of the number of page views of the second to last (full) quarter, compared with that of the last (full) quarter. If today was Aug 16th, 2022, the last complete quarter is Q2 (April, May, June). So it refers to the increment from Q1 to Q2, i.e., ( f(Q2) - f(Q1) ) ÷ f(Q1) x 100%.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastQuarterGrowth": 0.133542
+}
+```
+### wikipediaPageviewsLastYear
+  The number of views of its Wikipedia page of the last year if it exists.
+* **Type:** Integer
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastYear": 35770406
+}
+```
+### wikipediaPageviewsLastYearGrowth
+  The year over year growth of wikipediaPageviews, where we count the monthly-rolling increment of the year before last than the last year. It today was Aug 16th, 2022, it is computed by comparing the numbers from Aug 2021 to July 2022 and from Aug 2020 to July 2021, i.e., ( f(Aug 2021 to July 2022) - f(Aug 2020 to July 2021) ) ÷ f(Aug 2020 to July 2021) x 100%.
+* **Type:** Float
+* **Example:**
+```
+{
+	"wikipediaPageviewsLastYearGrowth": -0.29691178
+}
+```
diff --git a/docs/kg-ont-product.md b/docs/kg-ont-product.md
index bed66f2e..b25b2343 100644
--- a/docs/kg-ont-product.md
+++ b/docs/kg-ont-product.md
@@ -1,20 +1,32 @@
 ---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
 id: kg-ont-product
 title: Product
+generatedBy: generateOntology.js
 ---
 
-The product entity type encompasses products found throughout the web known to the Knowledge Graph. 
+The product entity type encompasses retail products found throughout the web known to the Knowledge Graph. 
 
 Note that fields are not guaranteed to exist in every entity record.
 
->New to the Diffbot Knowledge Graph? [Start here](dql-quickstart).
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
 
 ## Product Fields
 * [availability](#availability) 
 * [brand](#brand) 
 * [breadcrumb](#breadcrumb) 
 * [category](#category) 
+* [crawlTimestamp](#crawltimestamp) 
+* [diffbotUri](#diffboturi) 
 * [discussion](#discussion) 
+* [gs1Code](#gs1code) 
+* [gtin](#gtin) 
+* [id](#id) 
 * [images](#images) 
 * [isbn](#isbn) 
 * [language](#language) 
@@ -22,17 +34,20 @@ Note that fields are not guaranteed to exist in every entity record.
 * [multipleProducts](#multipleproducts) 
 * [offerPrice](#offerprice) 
 * [offerPriceDetails](#offerpricedetails) 
-* [prefixCode](#prefixcode) 
+* [pageUrl](#pageurl) 
 * [productId](#productid) 
 * [productOrigin](#productorigin) 
 * [regularPrice](#regularprice) 
 * [regularPriceDetails](#regularpricedetails) 
+* [resolvedPageUrl](#resolvedpageurl) 
 * [saveAmount](#saveamount) 
 * [saveAmountDetails](#saveamountdetails) 
 * [shippingAmount](#shippingamount) 
 * [sku](#sku) 
 * [text](#text) 
 * [title](#title) 
+* [type](#type) 
+* [types](#types) 
 * [upc](#upc) 
 
 ## Product Field Details
@@ -53,7 +68,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"brand": "Digital Decor"
+	"brand": "Monoprice"
 }
 ```
 ### breadcrumb
@@ -76,7 +91,25 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"category": "Indoor Living"
+	"category": "Electronics"
+}
+```
+### crawlTimestamp
+  Last time a site was crawled&#x2F;indexed
+* **Type:** Integer
+* **Example:**
+```
+{
+	"crawlTimestamp": 1758130421
+}
+```
+### diffbotUri
+  diffbotUri is a combination of an entityID and a corresponding web address or uniform resource identifier (URI), which is defined by appending the entityID to the URL https:&#x2F;&#x2F;www.diffbot.com&#x2F;entity&#x2F;. For example, Diffbot&#39;s entityID is CWSwJ_SWQPfqO3HQsxY4lGg and its DiffbotUri is https:&#x2F;&#x2F;www.diffbot.com&#x2F;entity&#x2F;CWSwJ_SWQPfqO3HQsxY4lGg
+* **Type:** String
+* **Example:**
+```
+{
+	"diffbotUri": "http://diffbot.com/entity/PRD140579625275"
 }
 ```
 ### discussion
@@ -86,146 +119,101 @@ Note that certain longer field examples may be truncated for readability.
 ```
 {
 	"discussion": {
-		"summary": "Digital Decor Set of Two (2) Premium Gold Down Alternative Sleeping Pillows PLUS 2 FREE Pillowcases",
-		"numPages": 1,
-		"image": "",
-		"name": "Digital Decor Set of Two (2) Premium Gold Down Alternative Sleeping Pillows PLUS 2 FREE Pillowcases",
-		"numPosts": 8,
-		"title": "Digital Decor Set of Two (2) Premium Gold Down Alternative Sleeping Pillows PLUS 2 FREE Pillowcases",
+		"nextPages": "",
+		"numPages": 0,
+		"provider": "",
+		"nextPage": "",
+		"language": "",
+		"numPosts": 0,
+		"title": "",
 		"posts": [
 			{
 				"date": {
-					"str": "d2017-06-29T00:00",
-					"precision": 4,
-					"timestamp": 1498694400000
-				},
-				"summary": "Because buy these.\nI'm a freak about my bed being my #1 spot for comfort. I've been using the same d...",
-				"image": "",
-				"author": "Jayme B",
-				"authorUrl": "https://www.amazon.com/gp/profile/amzn1.account.AGMHFY23GL6KJMTJCPDPAS6K7MYA/ref=cm_cr_dp_d_gw_tr?ie=UTF8",
-				"name": "Because buy these.\nI'm a freak...",
-				"language": "en",
-				"html": "<p>Because buy these.</p>\n<p>I'm a freak about my bed being my #1 spot for comfort. I've been using the same damn feather pillows almost five years, and I simply cannot take it anymore! They're so comfortable to sleep on (layered with multiple pillowcases to keep my face from getting poked by feathers), but they're such a mess! I think I'll find little feathers in my belongings forever until I die. They. Are. LITERALLY. Everywhere.</p>\n<p>Anyways, I purchased these pillows after reading reviews, which were obviously great considering I bought them, but I was still a skeptic because I was so used to sleeping on the same feather pillows for years. The packaging was really cute -- tied with a white, silky bow. Inside, the pillows were wrapped in plastic with all the air sucked out. They were completely flat, which made me nervous. I need fluffy. Still skeptical, but remembering the reviews said the pillows needed to be fluffed, I took them out of the plastic...</p>\n<p>EXPECTATIONS -- BLOWN. AWAY.</p>\n<p>They're just as soft, mushy, and all-around comfortable as my feathers pillows are. I can enjoy these and not getting stabbed in the face by feathers and still have the comfort of cuddling with a fluffy pillow!</p>\n<p>If you're a miserable person/like your pillows firm, you will hate this product. If you're a normal human-being, you'll be like me and write a review about them after opening because BUY THESE!</p>\n<p>In regard to price - these pillows cost at least half the price of my feather pillows. They also relieve some emotional stress because I no longer have to worry about finding new feathers stuck in my panties' fabric after wondering why I was feeling something prick me all day. 🙌🏼</p>",
-				"pageUrl": "https://www.amazon.com/Digital-Decor-Alternative-Sleeping-Pillowcases/dp/B017MA074Y",
-				"text": "Because buy these.\nI'm a freak about my bed being my #1 spot for comfort. I've been using the same damn feather pillows almost five years, and I simply cannot take it anymore! They're so comfortable to sleep on (layered with multiple pillowcases to keep my face from getting poked by feathers), but they're such a mess! I think I'll find little feathers in my belongings forever until I die. They. Are. LITERALLY. Everywhere.\nAnyways, I purchased these pillows after reading reviews, which were obviously great considering I bought them, but I was still a skeptic because I was so used to sleeping on the same feather pillows for years. The packaging was really cute -- tied with a white, silky bow. Inside, the pillows were wrapped in plastic with all the air sucked out. They were completely flat, which made me nervous. I need fluffy. Still skeptical, but remembering the reviews said the pillows needed to be fluffed, I took them out of the plastic...\nEXPECTATIONS -- BLOWN. AWAY.\nThey're just as soft, mushy, and all-around comfortable as my feathers pillows are. I can enjoy these and not getting stabbed in the face by feathers and still have the comfort of cuddling with a fluffy pillow!\nIf you're a miserable person/like your pillows firm, you will hate this product. If you're a normal human-being, you'll be like me and write a review about them after opening because BUY THESE!\nIn regard to price - these pillows cost at least half the price of my feather pillows. They also relieve some emotional stress because I no longer have to worry about finding new feathers stuck in my panties' fabric after wondering why I was feeling something prick me all day. 🙌🏼"
-			},
-			{
-				"date": {
-					"str": "d2017-06-01T00:00",
-					"precision": 4,
-					"timestamp": 1496275200000
-				},
-				"summary": "received a tiny box with 2 flat-as-a-pancake pillows folded in half. Was disappointed until I broke ...",
-				"image": "",
-				"author": "Amazon Customer",
-				"authorUrl": "https://www.amazon.com/gp/profile/amzn1.account.AE7TGXIJ7M6WRFLJ77XFNEELCPOA/ref=cm_cr_dp_d_gw_tr?ie=UTF8",
-				"name": "received a tiny box with 2 fla...",
-				"language": "en",
-				"html": "<p>received a tiny box with 2 flat-as-a-pancake pillows folded in half. Was disappointed until I broke the seal on the bag. I couldn't unpack them fast enough! Better than a down pillow by far. If you're expecting a firm pillow, don't order. BUT if you want plush and snuggly, this is perfect!!!! Is it available in king size?</p>",
-				"pageUrl": "https://www.amazon.com/Digital-Decor-Alternative-Sleeping-Pillowcases/dp/B017MA074Y",
-				"text": "received a tiny box with 2 flat-as-a-pancake pillows folded in half. Was disappointed until I broke the seal on the bag. I couldn't unpack them fast enough! Better than a down pillow by far. If you're expecting a firm pillow, don't order. BUT if you want plush and snuggly, this is perfect!!!! Is it available in king size?"
-			},
-			{
-				"date": {
-					"str": "d2017-07-10T00:00",
-					"precision": 4,
-					"timestamp": 1499644800000
-				},
-				"summary": "I hardly ever take the time to write reviews (sorry) but I just had to for these pillows. They are g...",
-				"image": "",
-				"author": "L",
-				"authorUrl": "https://www.amazon.com/gp/profile/amzn1.account.AHA2GWUY32DTXOWPJP3V76M7N4KA/ref=cm_cr_dp_d_gw_tr?ie=UTF8",
-				"name": "I hardly ever take the time to...",
-				"language": "en",
-				"html": "<p>I hardly ever take the time to write reviews (sorry) but I just had to for these pillows. They are great - very comfy and fluffy; they cradle your head perfectly without mushing down flat. I have neck issues, and these pillows keep my spine aligned without being too stiff. I ordered 6 to replace our pillows, and also some extra pillows. They were vacuum sealed and contained in a small box. So nice-they will be so easy to store - they don't take up much room. I placed my usual pillow cases over the ones that came with the pillows. I assume the extra cases will keep the pillows protected for longer.</p>",
-				"pageUrl": "https://www.amazon.com/Digital-Decor-Alternative-Sleeping-Pillowcases/dp/B017MA074Y",
-				"text": "I hardly ever take the time to write reviews (sorry) but I just had to for these pillows. They are great - very comfy and fluffy; they cradle your head perfectly without mushing down flat. I have neck issues, and these pillows keep my spine aligned without being too stiff. I ordered 6 to replace our pillows, and also some extra pillows. They were vacuum sealed and contained in a small box. So nice-they will be so easy to store - they don't take up much room. I placed my usual pillow cases over the ones that came with the pillows. I assume the extra cases will keep the pillows protected for longer."
-			},
-			{
-				"date": {
-					"str": "d2017-05-22T00:00",
-					"precision": 4,
-					"timestamp": 1495411200000
-				},
-				"summary": "Do not buy these. When I received these, the end seam was split on one pillow exposing stuffing. The...",
-				"image": "",
-				"author": "Margaret Godfrey",
-				"authorUrl": "https://www.amazon.com/gp/profile/amzn1.account.AF2FU53KMWBOGMYNAHKM4KE5OMDA/ref=cm_cr_dp_d_gw_tr?ie=UTF8",
-				"name": "Do not buy these. When I recei...",
-				"language": "en",
-				"html": "<p>Do not buy these. When I received these, the end seam was split on one pillow exposing stuffing. The pillow cases are extremely rough. All in all poor quality. I had overnight guests arriving and this was forced to see up pillow seam in order to use it.</p>",
-				"pageUrl": "https://www.amazon.com/Digital-Decor-Alternative-Sleeping-Pillowcases/dp/B017MA074Y",
-				"text": "Do not buy these. When I received these, the end seam was split on one pillow exposing stuffing. The pillow cases are extremely rough. All in all poor quality. I had overnight guests arriving and this was forced to see up pillow seam in order to use it."
-			},
-			{
-				"date": {
-					"str": "d2018-02-20T00:00",
-					"precision": 4,
-					"timestamp": 1519084800000
-				},
-				"summary": "I ordered these 2 pillows for my guest bedroom and they came super quickly (you can't beat the price...",
-				"image": "",
-				"author": "Bradley",
-				"authorUrl": "https://www.amazon.com/gp/profile/amzn1.account.AGL3Z5FQLJBNS43GKNO2OIYIHHRA/ref=cm_cr_dp_d_gw_tr?ie=UTF8",
-				"name": "I ordered these 2 pillows for ...",
-				"language": "en",
-				"html": "<p>I ordered these 2 pillows for my guest bedroom and they came super quickly (you can't beat the price either). They come vacuum sealed but upon opening them, within a few hours, they are large and plush. I didn't notice any smell, but before I used them I tossed them in the dryer (medium heat) with a damp towel and dryer sheet.</p>\n<p>These pillows are literally the definition of a standard pillow. Neither firm nor soft, they are the perfect balance of in-between if that's what you're looking for. I wouldn't want to sleep on them every single night, but they are great for a guest/spare bedroom.</p>",
-				"pageUrl": "https://www.amazon.com/Digital-Decor-Alternative-Sleeping-Pillowcases/dp/B017MA074Y",
-				"text": "I ordered these 2 pillows for my guest bedroom and they came super quickly (you can't beat the price either). They come vacuum sealed but upon opening them, within a few hours, they are large and plush. I didn't notice any smell, but before I used them I tossed them in the dryer (medium heat) with a damp towel and dryer sheet.\nThese pillows are literally the definition of a standard pillow. Neither firm nor soft, they are the perfect balance of in-between if that's what you're looking for. I wouldn't want to sleep on them every single night, but they are great for a guest/spare bedroom."
-			},
-			{
-				"date": {
-					"str": "d2017-02-02T00:00",
-					"precision": 4,
-					"timestamp": 1485993600000
-				},
-				"summary": "LOVE the pillows.. They are exactly as I thought they would be... I had to contact the Seller and th...",
-				"image": "",
-				"author": "brenda",
-				"authorUrl": "https://www.amazon.com/gp/profile/amzn1.account.AE7YYPF4VNJHQBXPYLEBVEUBJOMQ/ref=cm_cr_dp_d_gw_tr?ie=UTF8",
-				"name": "LOVE the pillows.. They are ex...",
-				"language": "en",
-				"html": "<p>LOVE the pillows.. They are exactly as I thought they would be... I had to contact the Seller and they are AWESOME people to do business with.. I would recommend these pillows to anyone.. Very pleased with them...</p>",
-				"pageUrl": "https://www.amazon.com/Digital-Decor-Alternative-Sleeping-Pillowcases/dp/B017MA074Y",
-				"text": "LOVE the pillows.. They are exactly as I thought they would be... I had to contact the Seller and they are AWESOME people to do business with.. I would recommend these pillows to anyone.. Very pleased with them..."
-			},
-			{
-				"date": {
-					"str": "d2017-06-07T00:00",
-					"precision": 4,
-					"timestamp": 1496793600000
+					"str": "",
+					"precision": 0,
+					"timestamp": 0
 				},
-				"summary": "These weren't bad pillows at all. The cases are a bit rough, but nothing a good washing didn't fix. ...",
-				"image": "",
-				"author": "Shade Koopa",
-				"authorUrl": "https://www.amazon.com/gp/profile/amzn1.account.AFJ42TVXCTZIRESNV7VXXRF5DGZA/ref=cm_cr_dp_d_gw_tr?ie=UTF8",
-				"name": "These weren't bad pillows at a...",
-				"language": "en",
-				"html": "<p>These weren't bad pillows at all. The cases are a bit rough, but nothing a good washing didn't fix. They did have a &quot;new pillow&quot; smell but again, washing or Febreze will take care of it. Comfortable to sleep on and didn't give me a headache like my usual standards pillow do. I don't see them lasting too long, but still a good pillow to have.</p>",
-				"pageUrl": "https://www.amazon.com/Digital-Decor-Alternative-Sleeping-Pillowcases/dp/B017MA074Y",
-				"text": "These weren't bad pillows at all. The cases are a bit rough, but nothing a good washing didn't fix. They did have a \"new pillow\" smell but again, washing or Febreze will take care of it. Comfortable to sleep on and didn't give me a headache like my usual standards pillow do. I don't see them lasting too long, but still a good pillow to have."
-			},
+				"sentiment": "",
+				"images": [
+					{
+						"displayHeight": 0,
+						"xpath": "",
+						"breadcrumb": [
+							{
+								"link": "",
+								"name": ""
+							}
+						],
+						"displayWidth": 0,
+						"naturalHeight": 0,
+						"language": "",
+						"links": "",
+						"anchorUrl": "",
+						"title": "",
+						"url": "",
+						"naturalWidth": 0,
+						"tags": [
+							{
+								"score": "",
+								"sentiment": "",
+								"types": "",
+								"count": 0,
+								"label": "",
+								"uri": ""
+							}
+						]
+					}
+				],
+				"author": "",
+				"authorUrl": "",
+				"language": "",
+				"html": "",
+				"pageUrl": "",
+				"text": ""
+			}
+		],
+		"tags": [
 			{
-				"date": {
-					"str": "d2017-07-21T00:00",
-					"precision": 4,
-					"timestamp": 1500595200000
-				},
-				"summary": "Poor quality outer fabric, not the same one ot the other, and smells terrible. No hotel i ever staye...",
-				"image": "",
-				"author": "Knobsandfaders",
-				"authorUrl": "https://www.amazon.com/gp/profile/amzn1.account.AGMCYVTORI7FEJAUHZLRCCOJXXWA/ref=cm_cr_dp_d_gw_tr?ie=UTF8",
-				"name": "Poor quality outer fabric, not...",
-				"language": "en",
-				"html": "<p>Poor quality outer fabric, not the same one ot the other, and smells terrible. No hotel i ever stayed in had such awful pillows. The end they are filled from is practically empty and the 'down alternative' doesnt seem to be able to be repositioned. Seems more like stuffing. The 'free pillow cases' are just more if the same awful fabric used as the outer pillow. Thin, rough, with dirt already on them. Really disappointed in this purchase. I don't underatand all the good reviews. They were very slow to ship so maybe they had to outsource to a bad factory someplace.</p>",
-				"pageUrl": "https://www.amazon.com/Digital-Decor-Alternative-Sleeping-Pillowcases/dp/B017MA074Y",
-				"text": "Poor quality outer fabric, not the same one ot the other, and smells terrible. No hotel i ever stayed in had such awful pillows. The end they are filled from is practically empty and the 'down alternative' doesnt seem to be able to be repositioned. Seems more like stuffing. The 'free pillow cases' are just more if the same awful fabric used as the outer pillow. Thin, rough, with dirt already on them. Really disappointed in this purchase. I don't underatand all the good reviews. They were very slow to ship so maybe they had to outsource to a bad factory someplace."
+				"score": "",
+				"sentiment": "",
+				"types": "",
+				"count": 0,
+				"label": "",
+				"uri": ""
 			}
 		],
-		"numParticipants": 8
+		"numParticipants": 0,
+		"rssUrl": ""
 	}
 }
 ```
+### gs1Code
+  
+* **Type:** String
+* **Example:**
+```
+{
+	"gs1Code": ""
+}
+```
+### gtin
+  
+* **Type:** String
+* **Example:**
+```
+{
+	"gtin": ""
+}
+```
+### id
+  Each entity in the Diffbot KnowledgeGraph (DKG) is identified by a unique identifier, an alphanumeric string like CWSwJ_SWQPfqO3HQsxY4lGg that uniquely identifies that entity. The id is directly derived from the most authoritative origin from the origins array.
+* **Type:** String
+* **Example:**
+```
+{
+	"id": "PRD08b7d187325e49e0e82be6322817c427"
+}
+```
 ### images
   
 * **Type:** GlobalIndexImage
@@ -235,11 +223,27 @@ Note that certain longer field examples may be truncated for readability.
 	"images": [
 		{
 			"summary": "",
-			"image": "https://images-na.ssl-images-amazon.com/images/I/51y5AzETmPL.jpg",
-			"naturalHeight": 379,
+			"naturalHeight": 0,
+			"name": "",
+			"image": "https://c1.neweggimages.com/productimage/nb640/A9HT_1_201812181560031897.jpg",
+			"url": "https://c1.neweggimages.com/productimage/nb640/A9HT_1_201812181560031897.jpg",
+			"naturalWidth": 0
+		},
+		{
+			"summary": "",
+			"naturalHeight": 0,
+			"name": "",
+			"image": "https://c1.neweggimages.com/productimage/nb640/A86ED2308171D4N7M72.jpg",
+			"url": "https://c1.neweggimages.com/productimage/nb640/A86ED2308171D4N7M72.jpg",
+			"naturalWidth": 0
+		},
+		{
+			"summary": "",
+			"naturalHeight": 0,
 			"name": "",
-			"url": "https://images-na.ssl-images-amazon.com/images/I/51y5AzETmPL.jpg",
-			"naturalWidth": 569
+			"image": "https://c1.neweggimages.com/productimage/nb640/A86ED230616083W2Z64.jpg",
+			"url": "https://c1.neweggimages.com/productimage/nb640/A86ED230616083W2Z64.jpg",
+			"naturalWidth": 0
 		}
 	]
 }
@@ -286,7 +290,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"offerPrice": "$18.99"
+	"offerPrice": ""
 }
 ```
 ### offerPriceDetails
@@ -296,28 +300,29 @@ Note that certain longer field examples may be truncated for readability.
 ```
 {
 	"offerPriceDetails": {
-		"symbol": "$",
-		"amount": 18.99,
-		"text": "$18.99"
+		"symbol": "",
+		"amount": "",
+		"text": "",
+		"currencyCode": ""
 	}
 }
 ```
-### prefixCode
-  
+### pageUrl
+  URL of submitted page &#x2F; page from which the entity is extracted
 * **Type:** String
 * **Example:**
 ```
 {
-	"prefixCode": ""
+	"pageUrl": "https://www.newegg.com/106526-monoprice-tilt-tv-wall-mount-bracket-for-tvs-32in-to-52in-max-weight-125lbs-vesa-patterns/p/169-0084-00069"
 }
 ```
 ### productId
-  
+**`Deprecated`**  
 * **Type:** String
 * **Example:**
 ```
 {
-	"productId": "B017MA074Y"
+	"productId": ""
 }
 ```
 ### productOrigin
@@ -335,7 +340,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"regularPrice": "$59.99"
+	"regularPrice": ""
 }
 ```
 ### regularPriceDetails
@@ -345,19 +350,29 @@ Note that certain longer field examples may be truncated for readability.
 ```
 {
 	"regularPriceDetails": {
-		"symbol": "$",
-		"amount": 59.99,
-		"text": "$59.99"
+		"symbol": "",
+		"amount": "",
+		"text": "",
+		"currencyCode": ""
 	}
 }
 ```
+### resolvedPageUrl
+  Returned if the pageUrl redirects to another URL
+* **Type:** String
+* **Example:**
+```
+{
+	"resolvedPageUrl": ""
+}
+```
 ### saveAmount
   
 * **Type:** String
 * **Example:**
 ```
 {
-	"saveAmount": "$41.00"
+	"saveAmount": ""
 }
 ```
 ### saveAmountDetails
@@ -367,9 +382,10 @@ Note that certain longer field examples may be truncated for readability.
 ```
 {
 	"saveAmountDetails": {
-		"symbol": "$",
-		"amount": 41,
-		"text": "$41.00"
+		"symbol": "",
+		"amount": "",
+		"text": "",
+		"currencyCode": ""
 	}
 }
 ```
@@ -388,7 +404,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"sku": "B017MA074Y"
+	"sku": "9SIA8SV3807097"
 }
 ```
 ### text
@@ -397,7 +413,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"text": "100% Cotton Hypoallergenic Outer Fabric\n Made in USA\n DREAMY RESTFUL SLUMBER: Sink into our sleeping pillows and drift to sleep on soft clouds of comfort!\n HIGH THREAD COUNT: Pillows for sleeping with a T200 thread count for coolness and breath-ability\n 100% HYPOALLERGENIC PILLOW: Dust Mite Resistant and Down alternative pillow - gentle Virgin Polyester filling. No Irritation\n EVERY KIND OF SLEEPER: Hotel & bed pillows perfect for all back, stomach & side sleepers out there!\n MADE IN USA QUALITY: A sleeping pillow you can count on - crafted from Made in US premium materials."
+	"text": "Buy Monoprice Tilting HDTV Wall Mount Bracket (max 125 lbs, 32~52\", VESA 100x100~500x400) with fast shipping and top-rated customer service. Once you know, you Newegg!"
 }
 ```
 ### title
@@ -406,7 +422,27 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"title": "Digital Decor Set of Two (2) Premium Gold Down Alternative Sleeping Pillows PLUS 2 FREE Pillowcases"
+	"title": "Monoprice Tilting HDTV Wall Mount Bracket (max 125 lbs, 32~52\", VESA 100x100~500x400)"
+}
+```
+### type
+  The top-level type of a Diffbot entity. Examples of type include Person, Organization, Article, Product.
+* **Type:** Type
+* **Example:**
+```
+{
+	"type": "Product"
+}
+```
+### types
+  There are tags.types which can only refer to dbpedia rdf types, while there are also the general DiffbotEntity types which is just an array of all the types an object belongs to. For instance a LocalBusiness would have &#x60;types:[&quot;Organization&quot;,&quot;LocalBusiness&quot;]&#x60; Finally, there are types that indicate a belonging to a subgroup such as business vs personal email address.
+* **Type:** String
+* **Example:**
+```
+{
+	"types": [
+		"Product"
+	]
 }
 ```
 ### upc
diff --git a/docs/kg-ont-research.md b/docs/kg-ont-research.md
new file mode 100644
index 00000000..dafe1ef8
--- /dev/null
+++ b/docs/kg-ont-research.md
@@ -0,0 +1,346 @@
+---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
+id: kg-ont-research
+title: Research
+generatedBy: generateOntology.js
+---
+
+The Research entity type includes public access research papers and journal articles found throughout the web and known to the Knowledge Graph. 
+
+Note that fields are not guaranteed to exist in every entity record.
+
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
+
+## Research Fields
+* [abstractText](#abstracttext) 
+* [author](#author) 
+* [authorUrl](#authorurl) 
+* [authors](#authors) 
+* [category](#category) 
+* [citedByCount](#citedbycount) 
+* [crawlTimestamp](#crawltimestamp) 
+* [date](#date) 
+* [diffbotUri](#diffboturi) 
+* [hasFullTextInRepository](#hasfulltextinrepository) 
+* [id](#id) 
+* [isOpenAccess](#isopenaccess) 
+* [language](#language) 
+* [openAccessStatus](#openaccessstatus) 
+* [openAccessUrl](#openaccessurl) 
+* [origins](#origins) 
+* [pageUrl](#pageurl) 
+* [pdfUrl](#pdfurl) 
+* [publisher](#publisher) 
+* [resolvedPageUrl](#resolvedpageurl) 
+* [tags](#tags) 
+* [text](#text) 
+* [title](#title) 
+* [type](#type) 
+* [types](#types) 
+* [url](#url) 
+
+## Research Field Details
+Note that certain longer field examples may be truncated for readability.
+
+### abstractText
+  The abstract of the article
+* **Type:** String
+* **Example:**
+```
+{
+	"abstractText": "Filipe Mesquita, Matteo Cannaviccio, Jordan Schmidek, Paramita Mirza, Denilson Barbosa. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019."
+}
+```
+### author
+  Author of the article
+* **Type:** String
+* **Example:**
+```
+{
+	"author": "Filipe Mesquita"
+}
+```
+### authorUrl
+  Author url
+* **Type:** String
+* **Example:**
+```
+{
+	"authorUrl": "https://api.openalex.org/authors/A5072734578"
+}
+```
+### authors
+  List of authors of the article
+* **Type:** GlobalIndexAuthor
+* **Example:**
+```
+{
+	"authors": [
+		{
+			"name": "Filipe Mesquita",
+			"link": "https://api.openalex.org/authors/A5072734578",
+			"institution": {
+				"name": "Menlo School",
+				"link": "http://diffbot.com/entity/Edh4LPutRPKSwA2QCVW9Qhw"
+			}
+		},
+		{
+			"name": "Matteo Cannaviccio",
+			"link": "https://api.openalex.org/authors/A5055764364",
+			"institution": {
+				"name": "Menlo School",
+				"link": "http://diffbot.com/entity/Edh4LPutRPKSwA2QCVW9Qhw"
+			}
+		},
+		{
+			"name": "Jordan Schmidek",
+			"link": "https://api.openalex.org/authors/A5079899001",
+			"institution": {
+				"name": "Menlo School",
+				"link": "http://diffbot.com/entity/Edh4LPutRPKSwA2QCVW9Qhw"
+			}
+		}
+	]
+}
+```
+### category
+  The category can be article, book-chapter, dissertation, book, dataset, paratext, report, reference-entry, peer-review or other
+* **Type:** String
+* **Example:**
+```
+{
+	"category": "article"
+}
+```
+### citedByCount
+  The citations received by the article
+* **Type:** Integer
+* **Example:**
+```
+{
+	"citedByCount": 43
+}
+```
+### crawlTimestamp
+  Last time a site was crawled&#x2F;indexed
+* **Type:** Integer
+* **Example:**
+```
+{
+	"crawlTimestamp": 1750204800
+}
+```
+### date
+  
+* **Type:** DDateTime
+* **Example:**
+```
+{
+	"date": {
+		"str": "d2019-01-01T00:00",
+		"precision": 4,
+		"timestamp": 1546300800000
+	}
+}
+```
+### diffbotUri
+  diffbotUri is a combination of an entityID and a corresponding web address or uniform resource identifier (URI), which is defined by appending the entityID to the URL https:&#x2F;&#x2F;www.diffbot.com&#x2F;entity&#x2F;. For example, Diffbot&#39;s entityID is CWSwJ_SWQPfqO3HQsxY4lGg and its DiffbotUri is https:&#x2F;&#x2F;www.diffbot.com&#x2F;entity&#x2F;CWSwJ_SWQPfqO3HQsxY4lGg
+* **Type:** String
+* **Example:**
+```
+{
+	"diffbotUri": "http://diffbot.com/entity/RCHEi3Kc_jqUPOGF1sk2oBfZHg"
+}
+```
+### hasFullTextInRepository
+  Whether or not the article has full text available in repository
+* **Type:** Boolean
+* **Example:**
+```
+{
+	"hasFullTextInRepository": false
+}
+```
+### id
+  Each entity in the Diffbot KnowledgeGraph (DKG) is identified by a unique identifier, an alphanumeric string like CWSwJ_SWQPfqO3HQsxY4lGg that uniquely identifies that entity. The id is directly derived from the most authoritative origin from the origins array.
+* **Type:** String
+* **Example:**
+```
+{
+	"id": "RCHEi3Kc_jqUPOGF1sk2oBfZHg"
+}
+```
+### isOpenAccess
+  Whether or not the article is open access
+* **Type:** Boolean
+* **Example:**
+```
+{
+	"isOpenAccess": false
+}
+```
+### language
+  Refers to the language in which an Article is written
+* **Type:** String
+* **Example:**
+```
+{
+	"language": "en"
+}
+```
+### openAccessStatus
+  Open access status - Gold: published in an DOAJ indexed OA journal, Green: toll-access on publisher page but free copy in OA repository, Hybrid: free under an open license in a toll-access journal, Bronze: free to read on publisher page but without any identifiable license, Closed: other articles
+* **Type:** String
+* **Example:**
+```
+{
+	"openAccessStatus": "hybrid"
+}
+```
+### openAccessUrl
+  Url which is open access
+* **Type:** String
+* **Example:**
+```
+{
+	"openAccessUrl": "https://www.aclweb.org/anthology/D19-1069.pdf"
+}
+```
+### origins
+  Origins of the research article
+* **Type:** String
+* **Example:**
+```
+{
+	"origins": [
+		"explore.openalex.org/works/W2970808735",
+		"zenodo.org/record/54328",
+		"doi.org/10.18653/v1/d19-1069"
+	]
+}
+```
+### pageUrl
+  URL of submitted page &#x2F; page from which the entity is extracted
+* **Type:** String
+* **Example:**
+```
+{
+	"pageUrl": "https://zenodo.org/record/54328"
+}
+```
+### pdfUrl
+  Pdf url of the article
+* **Type:** String
+* **Example:**
+```
+{
+	"pdfUrl": "https://www.aclweb.org/anthology/D19-1069.pdf"
+}
+```
+### publisher
+  The publisher of the article
+* **Type:** String
+* **Example:**
+```
+{
+	"publisher": "INFM-OAR (INFN Catania)"
+}
+```
+### resolvedPageUrl
+  Returned if the pageUrl redirects to another URL
+* **Type:** String
+* **Example:**
+```
+{
+	"resolvedPageUrl": ""
+}
+```
+### tags
+  Array of tags&#x2F;entities, generated from analysis of the extracted text and cross-referenced with DBpedia and other data sources. Language-specific tags will be returned if the source text is in English, Chinese, French, German, Spanish or Russian.
+* **Type:** GlobalIndexTag
+* **Example:**
+```
+{
+	"tags": [
+		{
+			"score": 0.81748056,
+			"types": [
+				"http://dbpedia.org/ontology/Work"
+			],
+			"label": "Benchmark (surveying)",
+			"uri": "http://diffbot.com/entity/E3fuo_p-hMy6W9j3odSS2iw"
+		},
+		{
+			"score": 0.6928679,
+			"types": [
+				"http://dbpedia.org/ontology/AcademicSubject",
+				"http://dbpedia.org/ontology/TopicalConcept",
+				"http://dbpedia.org/ontology/Skill"
+			],
+			"label": "Computer science",
+			"uri": "http://diffbot.com/entity/ETezqyVyRMgCMXNzqF5S5Mg"
+		},
+		{
+			"score": 0.52127504,
+			"types": [
+				"http://dbpedia.org/ontology/Algorithm",
+				"http://dbpedia.org/ontology/Skill"
+			],
+			"label": "Natural language processing",
+			"uri": "http://diffbot.com/entity/ENM9ojRqwMOS3bpIPkr4VHQ"
+		}
+	]
+}
+```
+### text
+  The full text of the article
+* **Type:** String
+* **Example:**
+```
+{
+	"text": "KnowledgeNet: A Benchmark Dataset for Knowledge Base Population\n\nKnowledgeNet: A Benchmark Dataset for Knowledge Base Population\n\nFilipe Mesquita, Matteo Cannaviccio,\nJordan Schmidek, Paramita Mirza\n\nDiffbot Technologies Corp.\nMenlo Park, California\n\n{filipe,matteo,jay,paramita}@diffbot.com\n\nDenilson Barbosa\nDepartment of Computing Science\n\nUniversity of Alberta\nEdmonton, Canada\n\ndenilson@ualberta.ca\n\nAbstract\n\nKnowledgeNet is a benchmark dataset for the\ntask of automatically populating a knowledge\nbase (Wikidata) with facts expressed in natural\nlanguage text on the web. KnowledgeNet pro-\nvides text exhaustively annotated with facts,\nthus enabling the holistic end-to-end evalua-\ntion of knowledge base population systems as\na whole, unlike previous benchmarks that are\nmore suitable for the evaluation of individ-\nual subcomponents (e.g., entity linking, rela-\ntion extraction). We discuss five baseline ap-\nproaches, where the best approach achieves an\nF1 score of 0.50, significantly outperforming a\ntraditional approach by 79% (0.28). However,\nour best baseline is far from reaching human\nperformance (0.82), indicating our dataset is\nchallenging. The KnowledgeNet dataset and\nbaselines are available at https://github.\ncom/diffbot/knowledge-net\n\n1 Introduction\n\nKnowledge Bases (KBs) are valuable resources\nfor developing intelligent applications, including\nsearch, question answering, data integration, and\nrecommendation systems. High-quality KBs still\nrely almost exclusively on human-curated struc-\ntured or semi-structured data. Such a reliance on\nhuman curation is a major obstacle to the creation\nof comprehensive, always-up-to-date KBs.\n\nKB population (KBP) is the task of automati-\ncally augmenting a KB with new facts. Tradition-\nally, KBP has been tackled with datasets for in-\ndividual components to be arranged in a pipeline,\ntypically: (1) entity discovery and linking (Ji et al.,\n2017; Shen et al., 2015) and (2) relation extrac-\ntion (Angeli et al., 2015; Zhang et al., 2017). En-\ntity discovery and linking seeks to recognize and\ndisambiguate proper names in text that refer to en-\ntities (e.g., people, organizations and locations) by\nlinking them to a reference KB. Relation extrac-\n\ntion seeks to detect facts involving two entities (or\nan entity and a literal, such as a number or date).\n\nKnowledgeNet is a benchmark dataset for pop-\nulating a KB (Wikidata) with facts expressed in\nnatural language on the web. KnowledgeNet facts\nare of the form (subject; property; object), where\nsubject and object are linked to Wikidata. For in-\nstance, the dataset contains text expressing the fact\n(Gennaro Basile1; RESIDENCE; Moravia2), in the\npassage:\n\n“Gennaro Basile was an Italian painter,\nborn in Naples but active in the German-\nspeaking countries. He settled at Brünn,\nin Moravia, and lived about 1756...”\n\nKnowledgeNet’s main goal is to evaluate the\noverall task of KBP rather than evaluating its sub-\ncomponents in separate. We refer to this type of\nevaluation as end-to-end. The dataset supports the\nend-to-end evaluation of KBP systems by exhaus-\ntively annotating all facts in a sentence. For in-\nstance, the dataset contains all RESIDENCE facts\n(two) from the sentence “He settled at Brünn, in\nMoravia, and lived about 1756”. This allows our\nevaluation to assess precision and recall of RESI-\n\nDENCE facts extracted from this sentence.\nA popular initiative to evaluate KBP is the\n\nText Analysis Conference, or TAC (Getman et al.,\n2018). TAC evaluations are performed manually\nand are hard to reproduce for new systems. Un-\nlike TAC, KnowledgeNet employs an automated\nand reproducible way to evaluate KBP systems\nat any time, rather than once a year. We hope a\nfaster evaluation cycle will accelerate the rate of\nimprovement for KBP.\n\nIn addition to providing an evaluation bench-\nmark, KnowledgeNet’s long-term goal is to pro-\nvide exhaustively annotated training data at large\n\n1http://www.wikidata.org/wiki/Q1367602\n2http://www.wikidata.org/wiki/Q43266\n\n\n\nscale. Our goal for the coming years is to annotate\n100,000 facts for 100 properties. To accomplish\nthis goal, we propose a new framework for anno-\ntating facts with high accuracy and low effort.\n\nContributions. Our contributions are as fol-\nlows. We introduce KnowledgeNet, a benchmark\ndataset for end-to-end evaluation of KBP systems\n(Section 3). We propose a new framework for\nexhaustive yet efficient annotation of facts (Sec-\ntion 3.1). We implement five baseline approaches\nthat build upon state-of-the-art KBP systems (Sec-\ntion 4). Finally, we present an experimental anal-\nysis of our baseline approaches, comparing their\nperformance to human performance (Section 5).\n\n2 Related Work\n\nKBP has traditionally been tackled with pipeline\nsystems. For instance, Stanford’s TAC 2015\nwinning system employs the following pipeline:\nnamed entity recognition (NER)→ entity linking\n→ relation extraction (Angeli et al., 2015). Stan-\nford’s latest TAC system continues to use the same\npipeline architecture with one additional com-\nponent: coreference resolution (Chaganty et al.,\n2017).\n\nThe main shortcoming of pipeline systems is er-\nror propagation. Mistakes made by components\nin the beginning of the pipeline are propagated to\nthe final output of the system, negatively affecting\nthe overall precision and recall. For instance, our\nexperiments show that the pipeline employed by\nStanford’s TAC 2015 winning system can achieve\na maximum recall of 0.32 in KnowledgeNet3.\n\nEnd-to-end systems (Liu et al., 2018; Miwa and\nBansal, 2016) are a promising solution for ad-\ndressing error propagation. However, a major\nroadblock for the advancement of this line of re-\nsearch is the lack of benchmark datasets. We hope\nKnowledgeNet can help support this line of re-\nsearch.\n\n2.1 Datasets\nTAC is a series of evaluation workshops organized\nas several tracks by NIST (Getman et al., 2018).\nThe Cold Start track provides an end-to-end eval-\nuation of KBP systems, while other tracks focus\non subtasks (e.g., entity disambiguation and link-\ning). The Cold Start track is the current standard\n\n3Maximum recall is the recall of candidate facts, which\nare used as input to the last component of the pipeline (rela-\ntion extraction).\n\nto evaluate KBP systems. To compete in this track,\nparticipants have a limited time window to submit\nthe results of their KBP systems. After this win-\ndow, the systems are evaluated by pooling facts\nextracted by the contestants. Despite its effec-\ntiveness for running a contest, this methodology\nhas been shown to be biased against new systems,\nwhich are not part of the pooling (Chaganty et al.,\n2017). TAC also manually evaluates a system’s\n“justification”, a span of text provided as evidence\nfor a fact. A correct fact with an incorrect justifica-\ntion is considered invalid. Therefore, reproducing\nTAC’s evaluation for new systems is challenging.\n\nWe propose KnowledgeNet as an automated\nand reproducible alternative to TAC’s evaluation.\nBefore creating KnowledgeNet, we considered us-\ning one of the datasets presented in Table 1. We\ncompare these datasets according to five criteria\nthat we consider desirable for a KBP benchmark\ndataset:\n\n• Human annotation: the dataset should be\nannotated by (multiple) humans to support\naccurate evaluation.\n\n• Exhaustive annotation: for each property,\nthe dataset should exhaustively enumerate all\nfacts of that property that are expressed in the\ntext. Exhaustive annotation allows measuring\ntrue precision and recall for a system.\n\n• Text annotation: the dataset should con-\ntain text spans for entities involved in a fact.\nThis allows evaluating whether the text ex-\npresses an extracted fact (as alternative to\nTAC’s manual justification assessments).\n\n• Links to reference KB: the dataset should\ncontain a link to the reference KB for entities\ninvolved in every fact (or indicate that such\nan entity doesn’t exist in the KB). This allows\nthe evaluation to confirm that the reference\nKB is being correctly populated.\n\n• Cross-sentence facts: the dataset should\ncontain facts involving entities whose names\nnever appear in the same sentence. This is be-\ncause a significant portion of facts expressed\nin text require coreference resolution of en-\ntity mentions spanning multiple sentences.\n\nACE 20054 is a popular dataset for end-to-\nend relation extraction systems (Li and Ji, 2014;\n\n4https://catalog.ldc.upenn.edu/\nLDC2006T06\n\n\n\nDataset KnowledgeNet ACE TAC TACRED FewRel DocRED GoogleRE T-REx\nHuman annotation yes yes yes yes yes yes yes no\nExhaustive annotation yes yes no no no no no no\nExhaus. anno. sentences 9,000 11,000 N/A N/A N/A N/A N/A N/A\nText span annotation yes yes no yes yes yes no yes\nLinks to reference KB yes yes yes no yes no yes yes\nCross-sentence facts yes yes yes no no yes yes yes\nAnnotated facts 13,000 8,000 84,000 22,000 56,000 56,000 40,000 11M\nProperties 15 18 41 41 100 96 5 353\nNew KB facts annotated 77% 100% 100% 100% 0% 100% 0% 0%\n\nTable 1: A dataset comparison according to our criteria for a desirable KBP benchmark dataset. “Exhaus. anno.\nsentences” shows the number of exhaustively annotated sentences. “New KB facts annotated” shows the percent-\nage of annotated facts that can be found in the reference KB. Most datasets contain only facts with no links to a\nreference KB (100% new facts) or contain only facts that exist in the KB (0% new facts).\n\nMiwa and Bansal, 2016). According to our crite-\nria, ACE might seem the most complete bench-\nmark dataset for end-to-end evaluation of KBP.\nIt exhaustively annotates every sentence of 599\ndocuments with mentions, coreference chains and\nfacts for 18 properties. Also, ACE has been inde-\npendently extended with links to Wikipedia (Ben-\ntivogli et al., 2010). However, a closer look at\nACE’s annotations reveals that most of them are\nill-suited for general-purpose KBs. These anno-\ntations include facts about broad properties (e.g.,\npart-whole, physical location) or mentions that do\nnot refer to named entities (e.g., “two Moroccan\nmen”, “women on the verge of fainting”, “African\nimmigrants who came ashore Thursday”). Per-\nhaps not coincidently, we are unaware of any work\nusing it for the purpose of evaluating a KBP sys-\ntem.\n\nOur annotation framework (Section 3.1) is in-\nspired by ACE’s framework but tailored towards\nKBP. First, we only annotate mentions that re-\nfer to named entities. Second, while our anno-\ntation is exhaustive, we focus on annotating sen-\ntences rather than documents, eliminating the need\nto annotate every fact described in the entire doc-\nument. Such a requirement creates a significant\nimbalance in the number of annotations per prop-\nerty. For instance, the most popular property from\nACE has 1,400 annotated facts, while the majority\nof properties from ACE have less than 300 anno-\ntated facts. This might explain why most relation\nextraction evaluations use only 6 properties from\nACE.\n\nAnnotating every sentence with facts for all\nproperties is also detrimental to the incremental\nnature of KnowledgeNet. Adding one property\nto the dataset would require an annotator to re-\nannotate every sentence in the dataset. In contrast,\n\nour framework selects a limited set of sentences\nto be annotated for a particular property. The re-\nmaining sentences are ignored during annotation\nand evaluation. As a consequence, our annotation\nframework allows incremental annotation of new\nproperties and is better suited for the goal of anno-\ntating 100,000 facts for 100 properties.\n\nDatasets employing non-exhaustive annotation.\nRecent datasets like T-REx automatically anno-\ntate facts in text as a way to produce training data\ncheaply. This is performed by aligning facts in\nthe KB to sentences referring to them (Elsahar\net al., 2018). Other datasets go further and use hu-\nman annotators to label every alignment as correct\nor incorrect. These semi-supervised datasets in-\nclude TACRED (Zhang et al., 2017), GoogleRE5,\nFewRel (Han et al., 2018) and DocRED (Yao\net al., 2019). Annotations created in this way are\nuseful for training KBP systems. However, they\ndo not provide an exhaustive annotation of facts,\nwhich is needed for end-to-end evaluation of KBP.\nFor instance, Zhang et al. (2017) train their KBP\nsystem with TACRED, but rely on TAC to evaluate\nthe system.\n\n3 KnowledgeNet Dataset\n\nThis section discusses the first release of Knowl-\nedgeNet and our annotation framework. The doc-\numents in this first release are either DBpedia ab-\nstracts (i.e., first paragraphs of a Wikipedia page)\nor short biographical texts about a person or or-\nganization from the web. These web texts were\ncollected using the Diffbot Knowledge Graph6.\n\nTable 2 presents the number of annotated facts\nfor each property. We chose 9,073 sentences\n\n5https://code.google.com/archive/p/\nrelation-extraction-corpus/downloads\n\n6https://www.diffbot.com/\n\n\n\nProperty Facts Sent. Relevant\nDATE OF BIRTH (PER–DATE) 761 731 468\nDATE OF DEATH (PER–DATE) 664 512 347\nRESIDENCE (PER–LOC) 1,456 796 387\nBIRTHPLACE (PER–LOC) 1137 936 407\nNATIONALITY (PER–LOC) 639 801 396\nEMPLOYEE OF (PER–ORG) 1,625 650 543\nEDUCATED AT (PER–ORG) 951 463 335\nPOLITICAL AFF. (PER–ORG) 635 537 318\nCHILD OF (PER–PER) 888 471 296\nSPOUSE (PER–PER) 1,338 504 298\nDATE FOUNDED (ORG–DATE) 500 543 315\nHEADQUARTERS (ORG–LOC) 880 564 296\nSUBSIDIARY OF (ORG–ORG) 544 481 299\nFOUNDED BY (ORG–PER) 764 558 346\nCEO (ORG–PER) 643 526 350\nTotal 13,425 9,073 5,423\n\nTable 2: KnowledgeNet properties and their number of\nannotated facts and sentences. “Relevant” indicates the\nnumber of relevant sentences (i.e., those with one or\nmore annotated facts). Subjects and objects belong to\none of the following types: person, organization, loca-\ntion and date.\n\nfrom 4,991 documents to be exhaustively anno-\ntated with facts about a particular property of in-\nterest. Because our annotation is exhaustive, neg-\native examples of facts can be automatically gen-\nerated. In total, KnowledgeNet comprises 13,425\nfacts from 15 properties.\n\nHoldout test set. We split the documents into\nfive folds in a round-robin manner, keeping the\nfifth fold (20% of the dataset) as the test set. To\npreserve the integrity of the results, we will release\nthe test set without annotations and will provide\na service through which others can evaluate their\nKBP systems. In our experiments, we used folds\n1-3 for training and fold 4 for development and\nvalidation, including hyperparameter tuning.\n\n3.1 Dataset Annotation\n\nThe dataset has been generated by multiple an-\nnotators using a new multi-step framework. We\nconjecture our framework can help annotators pro-\nduce higher quality annotations by allowing them\nto focus on one small, more specific task at a time.\nThe annotation consists of four different steps: (1)\nfetch sentences, (2) detect mentions, (3) classify\nfacts and (4) link entities.\n\nStep 1: Fetch sentences. We employ two meth-\nods of choosing a sentence for annotation. The\nfirst method leverages T-REx’s automatic align-\nments (Elsahar et al., 2018) to find sentences that\nare likely to describe facts from Wikidata. The\n\n(a) Interface to detect mentions of an entity type.\n\n(b) Interface to classify facts.\n\n(c) Interface to link a mention to a Wikidata entity.\n\nFigure 1: Interface for Steps 2-4 of our framework.\nStep 1 fetches sentences to be exhaustively annotated\nfor one property. The remaining steps guide annota-\ntors to detect entity mentions, facts and links in each\nsentence.\n\n\n\nsecond method chooses sentences that contain a\nkeyword that might indicate the presence of a fact\nfor a property (e.g., “born” for DATE OF BIRTH).\nWe have chosen these keywords by leveraging\nWikidata’s “also known as” values for properties\nas well as WordNet synonyms. By using these\nkeywords, we prevent the dataset to be exclusively\nannotated with facts that are known in Wikidata.\nIn fact, only 23% of facts annotated in this release\nare present in Wikidata.\n\nFor each fetched sentence, an annotator decides\nwhether the sentence is relevant for the property\nof interest (i.e., whether this sentence describes\none or more facts for this property). Relevant sen-\ntences go through steps 2 through 4; while irrel-\nevant sentences are kept to be used for detecting\nincorrectly extracted facts (i.e., false positives).\n\nIt is worth noting that this step might not fetch\nsome relevant sentences. Our framework does not\nrequire all relevant sentences to be annotated and\ndoes not penalize systems for extracting facts from\nsentences that were not annotated.\n\nStep 2: Detect mentions. In this step, we ask\nannotators to highlight entity names (Figure 1a).\nWe consider only entities whose type is relevant\nto the property being annotated. For instance, an\nannotator will only be asked to highlight names\nof people and organizations when annotating the\nproperty FOUNDED BY. Pronouns are automati-\ncally annotated with a gazetteer. To decrease the\nlikelihood of missing a mention, we consider the\nunion of mentions highlighted by two annotators\nfor the following step.\n\nStep 3: Classify facts. We ask annotators to\nclassify a candidate fact (i.e., a pair of mentions)\nin a sentence as a positive or negative example for\na property (Figure 1b). Each candidate fact is an-\nnotated by at least two annotators. A third anno-\ntator breaks the tie when the first two annotators\ndisagree.\n\nWe follow ACE’s reasonable reader rule,\nwhich states that a fact should only be annotated\nwhen there is no reasonable interpretation of the\nsentence in which the fact does not hold. In other\nwords, annotators are asked to only annotate facts\nthat are either explicitly stated in the sentence or\ninferred with absolute certainty from the sentence\nalone (i.e., without using external world knowl-\nedge).\n\nStep 4: Link entities. Finally, we ask annota-\ntors to link every mention involved in a fact to\na single Wikidata entity. In this step, annotators\ncan read the entire document and resolve mentions\n(e.g., pronouns) that refer to names in other sen-\ntences. Every mention is annotated by at least two\nannotators. When there is disagreement, we ask\nother annotators to join in the process until con-\nsensus is reached. In total, excluding the proper-\nties having literal objects (Table 2) we can assign\na link to both subject and object for 52% of the\nfacts.\n\nInter-annotator agreement. A total of five an-\nnotators have contributed to KnowledgeNet so far.\nIn Step 3, the initial two annotators have anno-\ntated 33,165 candidate facts with 96% agreement.\nThey disagreed on 1,495 candidate facts, where\n599 have been deemed positive by a third anno-\ntator. In Step 4, the initial two annotators have an-\nnotated 13,453 mentions with agreement of 93%.\nThe remaining 7% of mentions were resolved with\nadditional annotators.\n\nTiming. On average, annotating a sentence for\none property takes 3.9 minutes. This total time in-\ncludes two annotators (plus additional annotators\nfor tiebreaking). It also includes inspecting sen-\ntences that express no facts and therefore do not go\nthrough steps 2-4 (but are included in the dataset\nand are helpful for assessing false positives). The\nmost expensive step is Step 3 (40% of the total\ntime), followed by Step 4 (28%), Step 2 (22%) and\nStep 1 (10%).\n\n3.2 Limitations\nOur first release is comparable to other bench-\nmarks in size (e.g., ACE 2005), but it is perhaps\ninsufficient to train data-hungry models. This is\nby design. Most organizations do not have the re-\nsources to produce tens of thousands of examples\nfor each property of interest. As we expand the\nnumber of properties to achieve our goal of anno-\ntating 100,000 facts, we expect to keep the number\nof facts per property to around a thousand. In this\nway, we hope to promote approaches that can learn\nfrom multiple properties, requiring less annota-\ntions per property. We also hope to promote ap-\nproaches using KnowledgeNet together with semi-\nsupervised or unsupervised datasets for training.\n\nAnother limitation of our first release is the fo-\ncus on individual sentences. Currently, our frame-\nwork can only annotate a fact when the subject and\n\n\n\nthe object are explicitly mentioned by a name or\npronoun in a sentence. Others have reported that\nthe majority of facts fall into this category. For\nexample, the authors of DocRED report that 41%\nof facts require reasoning over multiple sentences\nin a document (Yao et al., 2019). This indicates\nthat a fact’s subject and object are mentioned by\ntheir full name in a single sentence 59% of the\ntime. The percentage of facts that can be anno-\ntated in KnowledgeNet is significantly higher than\n59%. This is because our framework can also an-\nnotate facts that require resolving (partial) names\nand pronouns referring to full names in other sen-\ntences. These facts are particularly common in our\ndocument collection.\n\n4 Baseline Approaches\n\nThis section presents five baseline approaches for\nKBP. We evaluate these approaches and compare\ntheir performance relative to human annotators in\nSection 5.\n\nFigure 2 illustrates the architecture shared by\nour five baseline approaches. We start by splitting\na given document into sentences. For each sen-\ntence, we detect entity mentions using a named\nentity recognizer (NER) and a gazetteer for pro-\nnoun mentions and their type (e.g., person, orga-\nnizations, location). We also detect coreference\nchains, that is, groups of mentions within a docu-\nment that refer to the same entity. Figure 2 illus-\ntrates how coreference chains help disambiguate\npronouns and partial names by clustering them to-\ngether with the full name of an entity. Finally, we\nlink these coreference chains to Wikidata entities.\n\nNext, we produce candidate facts by consider-\ning pair of mentions from the same sentence, as il-\nlustrated in Figure 2. The relation extraction com-\nponent makes the final decision on whether a can-\ndidate fact is expressed by the text.\n\n4.1 Relation Extraction\n\nFigure 2 illustrates our relation extraction model.\nThis model follow the literature by using a Bi-\nLSTM network (Miwa and Bansal, 2016; Xu et al.,\n2015; Zhou et al., 2016; Zhang et al., 2017), which\nis effective in capturing long-distance dependen-\ncies between words. We train a single multi-task\nmodel for all properties using both positive exam-\nples (i.e., annotated facts) and automatically gen-\nerated negative examples.\n\nThe model outputs two values for each property.\n\nThe first value represents the likelihood of the sub-\nject and object mentions (i.e., text spans) to be cor-\nrect, while the second value represents the likeli-\nhood of the subject and object links to be correct.\nWe learn individual thresholds for each value and\nproperty. When both values are above the thresh-\nold, the system outputs the fact with links. When\nthe first value is above the threshold and the sec-\nond value is below the threshold, we output the\nfact without links.\n\nFeatures. Figure 3 illustrates features encoding\nsyntactic and positional information, which are\nconcatenated to the embedding of every word.\n\n1. Enriched NER: NER label for names (us-\ning a NER system) and pronouns (using\ngazetteers for each type).\n\n2. Mention distance: distance between each\nword and the subject and object mention, fol-\nlowing Zhang et al. (2017).\n\n3. Shortest dependency path (SDP) length:\nnumber of edges in the SDP between the\nword and the subject and object.\n\n4. SDP distance: number of edges separating\nthe word to the closest word in the SDP be-\ntween the subject and object.\n\n5. Coreference confidence: confidence score\nof the coreference resolution system that a\nword refers to the subject and object.\n\n6. Coreference distance: distance to the clos-\nest mention in the coreference chain of the\nsubject and object.\n\n7. Coreference SDP length: number of edges\nin the SDP between the word and the closest\nmention in the subject and object chain.\n\n8. Coreference SDP distance: number of\nedges separating the word to the closest word\nin the SDP between the subject and object\ncoreference chains.\n\n9. KB entity types: entity types for the subject\nand object from Wikidata.\n\n10. KB properties: the property p where (sub-\nject; p; object) exists in Wikidata (when both\nthe subject and object have links).\n\n\n\nFigure 2: The architecture of our baseline approaches, illustrated with an example. Red arrows and boxes represent\ncoreference chains and blue arrows represent links to Wikidata. The subject and object of candidate facts are\nhighlighted in bold (blue) and italics (orange), respectively.\n\nFigure 3: Features representing the relationships be-\ntween the words. Significant relationships with the sub-\nject and object are highlighted in blue and orange, re-\nspectively.\n\nFeatures 9 and 10 are generated by querying\nWikidata and are relative to a single entity pair. We\nconcatenate those features to the Bi-LSTM output,\nas illustrated in Figure 2.\n\n4.2 Baseline Approaches\n\nWe propose five baselines obtained by improving\nthe candidate generation and relation extraction\ncomponents.\n\nBaseline 1. Our first baseline is a standard\npipeline approach inspired by the TAC 2015 Cold\nStart winning system (Angeli et al., 2015). It gen-\nerates candidate mentions by using NER and the\npronoun gazetteers. For mentions of the correct\ntype (e.g., person for the property SPOUSE), the sys-\ntem then links these mentions using an entity link-\ning system. The relation extraction component\nuses features 1-4.\n\nBaseline 2. Our second baseline adds corefer-\nence resolution. This baseline is inspired by Stan-\nford’s TAC 2017 system (Chaganty et al., 2017).\nWe leverage coreference chains to both increase\nthe number of candidate mentions linked to KB\nentities (e.g., pronouns) as well as to introduce ad-\nditional features. This model uses features 1-8.\n\nBaseline 3. Our third baseline adds features 9\nand 10 to the relation extraction model. These fea-\ntures leverage Wikidata information for the linked\nentities, such as entity types and known facts.\n\nBaseline 4. Our fourth baseline seeks to de-\ncrease error propagation by allowing more candi-\ndate facts to be evaluated by the relation extraction\ncomponent. This is done in two ways. First, Base-\nline 4 uses all mentions regardless of their NER\ntype when creating candidate facts. Second, this\nbaseline adds a candidate link to mentions that had\nno candidate link in Baseline 1-3 (due to incor-\nrect coreference chains). This is done by choos-\ning a link outside of the mention’s coreference\nchain that maximizes a combination of entity link-\ning score and coreference resolution score.\n\nBaseline 5. Our final baseline seeks to improve\nthe relation extraction component by employing\nBERT’s pre-trained representations (Devlin et al.,\n2018) in addition to all other features. To pro-\nduce a contextual representation for every word,\nwe learn a linear weighted combination of BERT’s\n12 layers, following Peters et al. (2019).\n\n\n\n4.3 Implementation\nAll our baseline systems follow the same ar-\nchitecture (Figure 2). We use spaCy7 for the\nNLP pipeline (sentence splitting, tokenization,\nPOS tagging, dependency parsing, NER), Hug-\nging Face’s coreference resolution system8, and\nthe Diffbot Entity Linker9 for entity linking.\n\nFor relation extraction we implement a standard\nBiLSTM network with two 500-dimensional hid-\nden layers. We use spaCy pre-trained word em-\nbeddings (size 300) concatenated with additional\nfeatures illustrated in Figure 3. The output of the\nBiLSTM network is concatenated with features\nfrom Wikidata (Features 9-10).\n\nWe train all the networks using mini-batches of\n128 examples and Adam optimizer (Kingma and\nBa, 2015) with a learning rate of 0.001. We use\nthe fourth fold of the dataset as validation set, se-\nlecting the model that minimize the loss function\nvalue. The same validation set is used to find\nthresholds for the output values that maximize the\nF1 score for each property.\n\n5 Experiments\n\nTable 3 presents the performance of our baseline\nsystems compared to the human performance. We\nreport precision (P ), recall (R) and F-score (F1):\n\nP =\ncorrectly extracted facts\n\nextracted facts\n,\n\nR =\ncorrectly extracted facts\n\nannotated facts\n,\n\nF1 =\n2 · P ·R\nP +R\n\n.\n\nWe evaluate our baseline systems from two per-\nspectives. The text evaluation deems an extracted\nfact correct when the text spans of the subject and\nobject overlap with the text spans of a ground truth\nfact. The link evaluation deems an extracted fact\ncorrect when the links of the subject and object\nmatch the links of a ground truth fact. In the link\nevaluation, we consider only facts where both the\nsubject and object links are present.\n\nHuman performance. To measure the human\nperformance on the end-to-end KBP task, one of\nour annotators was asked to enumerate all facts de-\nscribed in a sample of the test sentences. We re-\nport the performance of our annotator in Table 3.\n\n7https://spacy.io/\n8https://huggingface.co/coref/\n9https://diffbot.com/\n\nSystem Text evaluation Link evaluation\nP R F1 P R F1\n\nBaseline 1 0.44 0.64 0.52 0.31 0.26 0.28\nBaseline 2 0.49 0.64 0.55 0.37 0.32 0.34\nBaseline 3 0.47 0.66 0.55 0.35 0.37 0.36\nBaseline 4 0.60 0.65 0.62 0.51 0.48 0.49\nBaseline 5 0.68 0.70 0.69 0.53 0.48 0.50\nHuman 0.88 0.88 0.88 0.81 0.84 0.82\n\nTable 3: The performance of our baseline approaches\nis well below human performance.\n\nA closer look at the annotator’s mistakes shows\nthat 32% of the mistakes are due to incorrect an-\nnotations in KnowledgeNet (i.e., the annotator is\nactually correct). The remaining mistakes (68%)\nare mostly due to the annotator entering an in-\ncorrect fact (30%) or missing a link on a correct\nfact (18%). These results show that our annota-\ntion framework produces significantly better anno-\ntations than individual annotators working without\nour framework.\n\nBaseline performance. Table 3 presents the\nperformance of our baselines. Our best baseline\n(Baseline 5) significantly outperforms the standard\npipeline approach (Baseline 1) in both the text\nand link evaluation. However, the performance of\nBaseline 5 is well below the human performance.\nThe most impactful improvements over Baseline\n1 are due to (a) incorporating coreference when\nchoosing candidate links for pronouns in Baseline\n2; (b) allowing more candidate facts and links to\nbe classified by the relation extraction component\nin Baseline 4; and (c) incorporating BERT’s pre-\ntrained model in Baseline 5.\n\nTable 4 shows the “maximum recall” for each\nbaseline (i.e., recall of candidate facts used as in-\nput for the relation extraction component). These\nresults indicate that error propagation significantly\nlimits recall. Our best baseline shows higher max-\nimum recall due to coreference resolution (intro-\nduced in Baseline 2) and removing the filtering of\ncandidate facts based on NER types (introduced\nin Baseline 4). The low maximum recall for link\nevaluation is mainly due to incorrect candidate\nlinks, which can only be omitted (but not fixed)\nin our baselines.\n\n6 Conclusion\n\nWe introduce KnowledgeNet, an end-to-end\nbenchmark dataset for populating Wikidata with\nfacts expressed in natural language text on the\n\n\n\nSystem Text evaluation Link evaluation\nMaximum Recall Maximum Recall\n\nBaseline 1 0.80 0.33\nBaseline 2 0.80 0.37\nBaseline 3 0.80 0.37\nBaseline 4 0.90 0.59\nBaseline 5 0.90 0.59\n\nTable 4: The relation extraction component’s recall is\nlimited by error propagation. Maximum recall is the re-\ncall of the candidate facts used as input for the relation\nextraction component on the dev set.\n\nweb. We build KnowledgeNet using a new multi-\nstep framework that helps human annotators to\nproduce high-quality annotations efficiently. We\nalso introduce five baseline systems and evaluate\ntheir performance. Our best baseline outperforms\na traditional pipeline approach by 79% (F1 score\nof 0.50 vs. 0.28). Human performance is sig-\nnificantly higher (0.82), indicating that Knowled-\ngeNet can support further research to close this\ngap.\n\nOur experiments show that the traditional\npipeline approach for KB population is notably\nlimited by error propagation. Performance gains\nachieved by our best baseline are mainly due to\nmore candidates being passed along to the final\npipeline component (relation extraction), allow-\ning this component to fix errors made by previous\ncomponents. A closer inspection reveals that even\nour best baseline is fairly limited by error propa-\ngation and can only achieve a maximum recall of\n0.59. These results indicate that end-to-end mod-\nels might be a promising alternative to the tradi-\ntional pipeline approach.\n\nAcknowledgments\n\nWe would like to thank Veronica Romualdez and\nGeraldine Fajardo for their diligent annotation\nwork. We would also like to thank Mike Tung,\nZhaochen Guo, Sameer Singh and the anonymous\nreviewers for their helpful comments. This work\nwas supported by the Natural Sciences and En-\ngineering Research Council of Canada (NSERC)\nand Diffbot.\n\nReferences\n\nGabor Angeli, Victor Zhong, Danqi Chen, Arun Te-\njasvi Chaganty, Jason Bolton, Melvin Jose Johnson\nPremkumar, Panupong Pasupat, Sonal Gupta, and\nChristopher D. Manning. 2015. Bootstrapped self\n\ntraining for knowledge base population. In TAC.\nNIST.\n\nLuisa Bentivogli, Pamela Forner, Claudio Giu-\nliano, Alessandro Marchetti, Emanuele Pianta, and\nKateryna Tymoshenko. 2010. Extending English\nACE 2005 corpus annotation with ground-truth links\nto Wikipedia. In Proceedings of the 2nd Workshop\non The People’s Web Meets NLP: Collaboratively\nConstructed Semantic Resources, pages 19–27, Bei-\njing, China. Coling 2010 Organizing Committee.\n\nArun Chaganty, Ashwin Paranjape, Percy Liang, and\nChristopher D. Manning. 2017. Importance sam-\npling for unbiased on-demand evaluation of knowl-\nedge base population. In Proceedings of the 2017\nConference on Empirical Methods in Natural Lan-\nguage Processing, pages 1038–1048, Copenhagen,\nDenmark. Association for Computational Linguis-\ntics.\n\nJacob Devlin, Ming-Wei Chang, Kenton Lee, and\nKristina Toutanova. 2018. Bert: Pre-training of deep\nbidirectional transformers for language understand-\ning. In NAACL-HLT.\n\nHady Elsahar, Pavlos Vougiouklis, Arslen Remaci,\nChristophe Gravier, Jonathon Hare, Frederique\nLaforest, and Elena Simperl. 2018. T-REx: A large\nscale alignment of natural language with knowledge\nbase triples. In Proceedings of the 11th Language\nResources and Evaluation Conference, Miyazaki,\nJapan. European Language Resource Association.\n\nJeremy Getman, Joe Ellis, Stephanie Strassel, Zhiyi\nSong, and Jennifer Tracey. 2018. Laying the\nGroundwork for Knowledge Base Population: Nine\nYears of Linguistic Resources for TAC KBP. In\nProceedings of the Eleventh International Confer-\nence on Language Resources and Evaluation (LREC\n2018), Miyazaki, Japan. European Language Re-\nsources Association (ELRA).\n\nXu Han, Hao Zhu, Pengfei Yu, Ziyun Wang, Yuan Yao,\nZhiyuan Liu, and Maosong Sun. 2018. Fewrel: A\nlarge-scale supervised few-shot relation classifica-\ntion dataset with state-of-the-art evaluation. In Pro-\nceedings of the 2018 Conference on Empirical Meth-\nods in Natural Language Processing, Brussels, Bel-\ngium, October 31 - November 4, 2018, pages 4803–\n4809.\n\nHeng Ji, Xiaoman Pan, Boliang Zhang, Joel Nothman,\nJames Mayfield, Paul McNamee, and Cash Costello.\n2017. Overview of TAC-KBP2017 13 languages en-\ntity discovery and linking. In Proceedings of the\n2017 Text Analysis Conference, TAC 2017, Gaithers-\nburg, Maryland, USA, November 13-14, 2017.\n\nDiederik P. Kingma and Jimmy Ba. 2015. Adam: A\nmethod for stochastic optimization. In 3rd Inter-\nnational Conference on Learning Representations,\nICLR 2015, San Diego, CA, USA, May 7-9, 2015,\nConference Track Proceedings.\n\n\n\nQi Li and Heng Ji. 2014. Incremental joint extrac-\ntion of entity mentions and relations. In Proceed-\nings of the 52nd Annual Meeting of the Association\nfor Computational Linguistics (Volume 1: Long Pa-\npers), pages 402–412, Baltimore, Maryland. Asso-\nciation for Computational Linguistics.\n\nYue Liu, Tongtao Zhang, Zhicheng Liang, Heng Ji,\nand Deborah L. McGuinness. 2018. Seq2rdf: An\nend-to-end application for deriving triples from nat-\nural language text. In Proceedings of the ISWC\n2018 Posters & Demonstrations, Industry and Blue\nSky Ideas Tracks co-located with 17th International\nSemantic Web Conference (ISWC 2018), Monterey,\nUSA, October 8th - to - 12th, 2018.\n\nMakoto Miwa and Mohit Bansal. 2016. End-to-end re-\nlation extraction using lstms on sequences and tree\nstructures. pages 1105–1116.\n\nJeffrey Pennington, Richard Socher, and Christo-\npher D. Manning. 2014. Glove: Global vectors for\nword representation. In Empirical Methods in Nat-\nural Language Processing (EMNLP), pages 1532–\n1543.\n\nMatthew E. Peters, Sebastian Ruder, and Noah A.\nSmith. 2019. To tune or not to tune? adapt-\ning pretrained representations to diverse tasks. In\nProceedings of the 4th Workshop on Representa-\ntion Learning for NLP, RepL4NLP@ACL 2019, Flo-\nrence, Italy, August 2, 2019., pages 7–14.\n\nPouya Pezeshkpour, Liyan Chen, and Sameer\nSingh. 2018. Embedding multimodal relational\ndata for knowledge base completion. CoRR,\nabs/1809.01341.\n\nWei Shen, Jianyong Wang, and Jiawei Han. 2015. En-\ntity linking with a knowledge base: Issues, tech-\nniques, and solutions. IEEE Trans. Knowl. Data\nEng., 27(2):443–460.\n\nQuan Wang, Zhendong Mao, Bin Wang, and Li Guo.\n2017. Knowledge graph embedding: A survey of\napproaches and applications. IEEE Trans. Knowl.\nData Eng., 29(12):2724–2743.\n\nPeng Xu and Denilson Barbosa. 2019. Connecting lan-\nguage and knowledge with heterogeneous represen-\ntations for neural relation extraction. In Proceed-\nings of the 2019 Conference of the North American\nChapter of the Association for Computational Lin-\nguistics: Human Language Technologies, NAACL-\nHLT 2019, Minneapolis, Minnesota, USA, June 2-7,\n2019, Volume 2 (Short Papers), page 4.\n\nYan Xu, Lili Mou, Ge Li, Yunchuan Chen, Hao Peng,\nand Zhi Jin. 2015. Classifying relations via long\nshort term memory networks along shortest depen-\ndency paths. In Proceedings of the 2015 Confer-\nence on Empirical Methods in Natural Language\nProcessing, pages 1785–1794, Lisbon, Portugal. As-\nsociation for Computational Linguistics.\n\nYuan Yao, Deming Ye, Peng Li, Xu Han, Yankai Lin,\nZhenghao Liu, Zhiyuan Liu, Lixin Huang, Jie Zhou,\nand Maosong Sun. 2019. Docred: A large-scale\ndocument-level relation extraction dataset. In Pro-\nceedings of the 57th Conference of the Association\nfor Computational Linguistics, ACL 2019, Florence,\nItaly, July 28- August 2, 2019, Volume 1: Long Pa-\npers, pages 764–777.\n\nYuhao Zhang, Victor Zhong, Danqi Chen, Gabor An-\ngeli, and Christopher D. Manning. 2017. Position-\naware attention and supervised data improve slot fill-\ning. In Proceedings of the 2017 Conference on Em-\npirical Methods in Natural Language Processing,\npages 35–45, Copenhagen, Denmark. Association\nfor Computational Linguistics.\n\nPeng Zhou, Wei Shi, Jun Tian, Zhenyu Qi, Bingchen\nLi, Hongwei Hao, and Bo Xu. 2016. Attention-\nbased bidirectional long short-term memory net-\nworks for relation classification. In Proceedings of\nthe 54th Annual Meeting of the Association for Com-\nputational Linguistics (Volume 2: Short Papers),\npages 207–212, Berlin, Germany. Association for\nComputational Linguistics.\n\nA Beyond Binary Relationships\n\nWhile it would be convenient to express all facts\nas (subject; property; object) triples, this is not al-\nways possible. Many facts require further annota-\ntions to be sufficiently and accurately expressed\nin the KB. Take for instance (United States;\nhead of government; Barack Obama), which only\nholds true in the past.\n\nQualifiers allow facts to be expanded or contex-\ntualized beyond what can be expressed with binary\nrelationships. More specifically, qualifiers can be\nused to constrain the validity of a fact in time or\nspace, e.g., (employment fact; end time; 2017);\nrepresent n-ary relationships, e.g., (casting fact;\ncharacter role; Tony Stark); and track provenance.\n\nThis release contains 4,518 facts annotated\nwith three temporal qualifiers: IS CURRENT,\nSTART TIME and END TIME. We use one of our\nbaseline system to obtain facts to be annotated\nwith qualifiers, along with the the sentence where\neach fact was found. Given a fact and a sentence,\nhuman annotators must decide the value of a quali-\nfier (true or false for IS CURRENT or a time expres-\nsion for START TIME, END TIME). A third option\nunclear can be chosen in the case of uncertainty.\nTo be included in the dataset, each fact must be\nannotated by two annotators in agreement. While\npreliminary experiments show promising results\nfor qualifier extraction, they are out-of-scope of\nthis work.\n\n\n"
+}
+```
+### title
+  Title of the article
+* **Type:** String
+* **Example:**
+```
+{
+	"title": "KnowledgeNet: A Benchmark Dataset for Knowledge Base Population"
+}
+```
+### type
+  The top-level type of a Diffbot entity. Examples of type include Person, Organization, Article, Product.
+* **Type:** Type
+* **Example:**
+```
+{
+	"type": "Research"
+}
+```
+### types
+  There are tags.types which can only refer to dbpedia rdf types, while there are also the general DiffbotEntity types which is just an array of all the types an object belongs to. For instance a LocalBusiness would have &#x60;types:[&quot;Organization&quot;,&quot;LocalBusiness&quot;]&#x60; Finally, there are types that indicate a belonging to a subgroup such as business vs personal email address.
+* **Type:** String
+* **Example:**
+```
+{
+	"types": [
+		"Research"
+	]
+}
+```
+### url
+  Page url of the article
+* **Type:** String
+* **Example:**
+```
+{
+	"url": "https://explore.openalex.org/works/W2970808735"
+}
+```
diff --git a/docs/kg-ont-video.md b/docs/kg-ont-video.md
index 4b48bc50..0a12995d 100644
--- a/docs/kg-ont-video.md
+++ b/docs/kg-ont-video.md
@@ -1,27 +1,41 @@
 ---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
 id: kg-ont-video
 title: Video
+generatedBy: generateOntology.js
 ---
 
 The Video entity type encompasses videos found throughout the web and known to the Knowledge Graph. 
 
 Note that fields are not guaranteed to exist in every entity record.
 
->New to the Diffbot Knowledge Graph? [Start here](dql-quickstart).
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
 
 ## Video Fields
 * [author](#author) 
+* [crawlTimestamp](#crawltimestamp) 
 * [date](#date) 
+* [diffbotUri](#diffboturi) 
 * [duration](#duration) 
 * [embedUrl](#embedurl) 
 * [html](#html) 
+* [id](#id) 
 * [images](#images) 
 * [language](#language) 
 * [mime](#mime) 
 * [naturalHeight](#naturalheight) 
 * [naturalWidth](#naturalwidth) 
+* [pageUrl](#pageurl) 
+* [resolvedPageUrl](#resolvedpageurl) 
 * [text](#text) 
 * [title](#title) 
+* [type](#type) 
+* [types](#types) 
 * [url](#url) 
 * [viewCount](#viewcount) 
 
@@ -34,7 +48,16 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"author": "Io-Tahoe"
+	"author": ""
+}
+```
+### crawlTimestamp
+  Last time a site was crawled&#x2F;indexed
+* **Type:** Integer
+* **Example:**
+```
+{
+	"crawlTimestamp": 1745910773
 }
 ```
 ### date
@@ -44,19 +67,28 @@ Note that certain longer field examples may be truncated for readability.
 ```
 {
 	"date": {
-		"str": "d2018-12-12T00:00",
-		"precision": 4,
-		"timestamp": 1544572800000
+		"str": "",
+		"precision": 0,
+		"timestamp": 0
 	}
 }
 ```
+### diffbotUri
+  diffbotUri is a combination of an entityID and a corresponding web address or uniform resource identifier (URI), which is defined by appending the entityID to the URL https:&#x2F;&#x2F;www.diffbot.com&#x2F;entity&#x2F;. For example, Diffbot&#39;s entityID is CWSwJ_SWQPfqO3HQsxY4lGg and its DiffbotUri is https:&#x2F;&#x2F;www.diffbot.com&#x2F;entity&#x2F;CWSwJ_SWQPfqO3HQsxY4lGg
+* **Type:** String
+* **Example:**
+```
+{
+	"diffbotUri": "http://diffbot.com/entity/VID199193048060"
+}
+```
 ### duration
   
 * **Type:** Integer
 * **Example:**
 ```
 {
-	"duration": 2964
+	"duration": 0
 }
 ```
 ### embedUrl
@@ -74,7 +106,16 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"html": "<video controls><source src=\"https://r4---sn-vgqs7ns7.googlevideo.com/videoplayback?ratebypass=yes&mm=31%2C29&dur=2964.096&lmt=1544647458750109&c=WEB&signature=BDFC5B6365BCB570015CF0DB39639303EE480D2E.A2568676D096E9103EAC2689DCDB93658447CFF9&txp=2211222&itag=22&expire=1547667225&fvip=3&id=o-AAMvdWHz8tI28JlykIQJzVRSY-s917ZTmeSL3h6iFYRV&mime=video%2Fmp4&source=youtube&key=yt6&mn=sn-vgqs7ns7%2Csn-vgqsener&ei=uDI_XMrOOJWYigTdq4n4Cg&ms=au%2Crdu&requiressl=yes&sparams=dur%2Cei%2Cid%2Cip%2Cipbits%2Citag%2Clmt%2Cmime%2Cmm%2Cmn%2Cms%2Cmv%2Cpl%2Cratebypass%2Crequiressl%2Csource%2Cexpire&ipbits=0&pl=16&mv=m&ip=35.232.157.82&mt=1547645504\" type=\"video/mp4\"></video><p>It is undeniable that the amount and complexity of data is growing within the modern enterprise. But why and what to do about it is the question that every enterprise leader must now face.\n\nIn this insightful and thought-provoking webinar, we will deconstruct what is fueling data growth and increased data complexity, the approaches organizations have used to deal with the challenges that this growth brings, and why the only hope for dealing with it in the future may be smart data discovery approaches powered by artificial intelligence (AI).\n\nKey topics that will be discussed during this webinar are:\n\n• Why traditional data discovery no longer works\n• Why AI may be the answer or part of the solution\n• Why self-service is a strategic imperative\n• An executive's perspective\n\nBe sure to like and subscribe to our channel for more webinar videos!\n\nVisit our website https://io-tahoe.com to learn more about Io-Tahoe's Smart Data Discovery platforms.\n\n\nFollow us on Twitter at: https://twitter.com/iotahoe\n\nFollow us on LinkedIn at: https://www.linkedin.com/company/9194521\n\nLike us on Facebook at: https://www.facebook.com/iotahoe\n\nFollow us on Instagram at: https://instagram.com/iotahoe</p>"
+	"html": ""
+}
+```
+### id
+  Each entity in the Diffbot KnowledgeGraph (DKG) is identified by a unique identifier, an alphanumeric string like CWSwJ_SWQPfqO3HQsxY4lGg that uniquely identifies that entity. The id is directly derived from the most authoritative origin from the origins array.
+* **Type:** String
+* **Example:**
+```
+{
+	"id": "VID199193048060"
 }
 ```
 ### images
@@ -85,11 +126,32 @@ Note that certain longer field examples may be truncated for readability.
 {
 	"images": [
 		{
-			"summary": "",
-			"image": "https://i.ytimg.com/vi/-w6blCJ0CTY/maxresdefault.jpg",
-			"name": "Deconstructing Data Complexity and the Case for AI-Driven Smart Data Discovery",
-			"title": "Deconstructing Data Complexity and the Case for AI-Driven Smart Data Discovery",
-			"url": "https://i.ytimg.com/vi/-w6blCJ0CTY/maxresdefault.jpg"
+			"displayHeight": 0,
+			"xpath": "",
+			"breadcrumb": [
+				{
+					"link": "",
+					"name": ""
+				}
+			],
+			"displayWidth": 0,
+			"naturalHeight": 0,
+			"language": "",
+			"links": "",
+			"anchorUrl": "",
+			"title": "",
+			"url": "",
+			"naturalWidth": 0,
+			"tags": [
+				{
+					"score": "",
+					"sentiment": "",
+					"types": "",
+					"count": 0,
+					"label": "",
+					"uri": ""
+				}
+			]
 		}
 	]
 }
@@ -100,7 +162,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"language": "en"
+	"language": "zh"
 }
 ```
 ### mime
@@ -109,7 +171,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"mime": "video/mp4"
+	"mime": ""
 }
 ```
 ### naturalHeight
@@ -118,7 +180,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"naturalHeight": 720
+	"naturalHeight": 0
 }
 ```
 ### naturalWidth
@@ -127,7 +189,25 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"naturalWidth": 1280
+	"naturalWidth": 0
+}
+```
+### pageUrl
+  URL of submitted page &#x2F; page from which the entity is extracted
+* **Type:** String
+* **Example:**
+```
+{
+	"pageUrl": "https://blog.csdn.net/cgsayuclv/article/details/144147799"
+}
+```
+### resolvedPageUrl
+  Returned if the pageUrl redirects to another URL
+* **Type:** String
+* **Example:**
+```
+{
+	"resolvedPageUrl": ""
 }
 ```
 ### text
@@ -136,7 +216,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"text": "It is undeniable that the amount and complexity of data is growing within the modern enterprise. But why and what to do about it is the question that every enterprise leader must now face.\n\nIn this insightful and thought-provoking webinar, we will deconstruct what is fueling data growth and increased data complexity, the approaches organizations have used to deal with the challenges that this growth brings, and why the only hope for dealing with it in the future may be smart data discovery approaches powered by artificial intelligence (AI).\n\nKey topics that will be discussed during this webinar are:\n\n• Why traditional data discovery no longer works\n• Why AI may be the answer or part of the solution\n• Why self-service is a strategic imperative\n• An executive's perspective\n\nBe sure to like and subscribe to our channel for more webinar videos!\n\nVisit our website https://io-tahoe.com to learn more about Io-Tahoe's Smart Data Discovery platforms.\n\n\nFollow us on Twitter at: https://twitter.com/iotahoe\n\nFollow us on LinkedIn at: https://www.linkedin.com/company/9194521\n\nLike us on Facebook at: https://www.facebook.com/iotahoe\n\nFollow us on Instagram at: https://instagram.com/iotahoe"
+	"text": ""
 }
 ```
 ### title
@@ -145,7 +225,27 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"title": "Deconstructing Data Complexity and the Case for AI-Driven Smart Data Discovery"
+	"title": "利用Diffbot Extract API提取和处理网页数据的完整指南-CSDN博客"
+}
+```
+### type
+  The top-level type of a Diffbot entity. Examples of type include Person, Organization, Article, Product.
+* **Type:** Type
+* **Example:**
+```
+{
+	"type": "Video"
+}
+```
+### types
+  There are tags.types which can only refer to dbpedia rdf types, while there are also the general DiffbotEntity types which is just an array of all the types an object belongs to. For instance a LocalBusiness would have &#x60;types:[&quot;Organization&quot;,&quot;LocalBusiness&quot;]&#x60; Finally, there are types that indicate a belonging to a subgroup such as business vs personal email address.
+* **Type:** String
+* **Example:**
+```
+{
+	"types": [
+		"Video"
+	]
 }
 ```
 ### url
@@ -154,7 +254,7 @@ Note that certain longer field examples may be truncated for readability.
 * **Example:**
 ```
 {
-	"url": "https://r4---sn-vgqs7ns7.googlevideo.com/videoplayback?ratebypass=yes&mm=31%2C29&dur=2964.096&lmt=1544647458750109&c=WEB&signature=BDFC5B6365BCB570015CF0DB39639303EE480D2E.A2568676D096E9103EAC2689DCDB93658447CFF9&txp=2211222&itag=22&expire=1547667225&fvip=3&id=o-AAMvdWHz8tI28JlykIQJzVRSY-s917ZTmeSL3h6iFYRV&mime=video%2Fmp4&source=youtube&key=yt6&mn=sn-vgqs7ns7%2Csn-vgqsener&ei=uDI_XMrOOJWYigTdq4n4Cg&ms=au%2Crdu&requiressl=yes&sparams=dur%2Cei%2Cid%2Cip%2Cipbits%2Citag%2Clmt%2Cmime%2Cmm%2Cmn%2Cms%2Cmv%2Cpl%2Cratebypass%2Crequiressl%2Csource%2Cexpire&ipbits=0&pl=16&mv=m&ip=35.232.157.82&mt=1547645504"
+	"url": ""
 }
 ```
 ### viewCount
diff --git a/docs/kg-technology-categories-list.md b/docs/kg-technology-categories-list.md
new file mode 100644
index 00000000..3e0a4b87
--- /dev/null
+++ b/docs/kg-technology-categories-list.md
@@ -0,0 +1,1016 @@
+---
+id: kg-technology-categories-list
+title: Technology Categories
+onPageNav: false
+---
+
+The list below outlines all possible categories that may be returned within the `technographics` attribute in Organization entity types. A list of all categories may also be accessed as their own entity type (`type:TechnologyCategory`) or found in the `technologyCategories` attribute in its parent `type:Technology`. See the DQL examples below for more color.
+
+```python
+# To find organizations that use "Assisted Living Software"
+type:Organization technographics.categories:"Assisted Living Software"
+```
+
+```python
+# To find all technologies associated with the technology category "Real Estate Agency Software"
+type:Technology technologyCategories:"Real Estate Agency Software"
+```
+
+| Primary Category    | Secondary Category | Tertiary Category                   |  Quaternary Category |
+| ------------------- | ------------------ | ----------------------------------- | ---- |
+|  Aerospace technologies         |                   |   |  |
+|  Agricultural technology         |                   |   |  |
+|  Aircraft by type         |                   |   |  |
+|  Assistive technology         |                   |   |  |
+|  Balancing technology         |                   |   |  |
+|  Banking technology         |                   |   |  |
+|  Biotechnology         |                   |   |  |
+|  Building technology         |                   |   |  |
+|  Chemical looping technologies         |                   |   |  |
+|  Cleaning methods         |                   |   |  |
+|  Cleanroom technology         |                   |   |  |
+|  Computer storage technologies         |                   |   |  |
+|  Computers         |                   |   |  |
+|  Construction         |                   |   |  |
+|  Cooling technology         |                   |   |  |
+|  Cybernetics         |                   |   |  |
+|  Drilling technology         |                   |   |  |
+|  Educational technology         |                   |   |  |
+|  Electronics         |                   |   |  |
+|  Emerging technologies         |                   |   |  |
+|  Energy         |                   |   |  |
+|  Energy technology         |                   |   |  |
+|  Engine technology         |                   |   |  |
+|  Environmental technology         |                   |   |  |
+|  Equipment         |                   |   |  |
+|  Explosives         |                   |   |  |
+|  Film and video technology         |                   |   |  |
+|  Financial technology         |                   |   |  |
+|  Fluid technology         |                   |   |  |
+|  Food technology         |                   |   |  |
+|  Gambling technology         |                   |   |  |
+|  Gas turbine technology         |                   |   |  |
+|  Geographical technology         |                   |   |  |
+|  Haptic technology         |                   |   |  |
+|  Home automation         |                   |   |  |
+|  Information and communications technology         |                   |   |  |
+|  Infrared technology         |                   |   |  |
+|  Instant messaging         |                   |   |  |
+|  Inventions         |                   |   |  |
+|  Machinery         |                   |   |  |
+|  Manufacturing         |                   |   |  |
+|  Medical technology         |                   |   |  |
+|  Microtechnology         |                   |   |  |
+|  Military technology         |                   |   |  |
+|  Mining techniques         |                   |   |  |
+|  Missile technology         |                   |   |  |
+|  Motor vehicles         |                   |   |  |
+|  Music technology         |                   |   |  |
+|  Nanotechnology         |                   |   |  |
+|  Oils and fats technologies         |                   |   |  |
+|  Operating system technology         |                   |   |  |
+|  Particle technology         |                   |   |  |
+|  Political campaign technology         |                   |   |  |
+|  Pollution control technologies         |                   |   |  |
+|  Primitive technology         |                   |   |  |
+|  Push technology         |                   |   |  |
+|  Rail technologies         |                   |   |  |
+|  Scientific equipment         |                   |   |  |
+|  Security technology         |                   |   |  |
+|  Software         |                   |   |  |
+|          |  AB Testing Software                 |  |  |
+|          |  AI Writing Assistant Software                 |  |  |
+|          |  AIOps Platforms Software                 |  |  |
+|          |  AML Software                 |  |  |
+|          |  API Management Software                 |  |  |
+|          |  Absence Management Software                 |  |  |
+|          |  Access Governance Software                 |  |  |
+|          |  Account Based Marketing Software                 |  |  |
+|          |  Accounting Practice Management Software                 |  |  |
+|          |  Accounting Software                 |  |  |
+|          |  Accounts Payable Software                 |  |  |
+|          |  Accounts Receivable Software                 |  |  |
+|          |  Accreditation Management Software                 |  |  |
+|          |  Ad Server Software                 |  |  |
+|          |  Address Verification Software                 |  |  |
+|          |  Admissions Software                 |  |  |
+|          |  Advertising Agency Software                 |  |  |
+|          |  Advocacy Software                 |  |  |
+|          |  Affiliate Software                 |  |  |
+|          |  Airline Reservation System                 |  |  |
+|          |  Alumni Management Software                 |  |  |
+|          |  Analytics                 |  |  |
+|          |  Analytics Software                 |  |  |
+|          |  Android Kiosk Software                 |  |  |
+|          |  Animal Shelter Software                 |  |  |
+|          |  Animation Software                 |  |  |
+|          |  Antispam Software                 |  |  |
+|          |  App Building Software                 |  |  |
+|          |  App Design Software                 |  |  |
+|          |  Apparel Management Software                 |  |  |
+|          |  Applicant Tracking Software                 |  |  |
+|          |  Application Development Software                 |  |  |
+|          |  Application Lifecycle Management Software                 |  |  |
+|          |  Application Performance Management Software                 |  |  |
+|          |  Applied Behavior Analysis                 |  |  |
+|          |  Appointment Reminder Software                 |  |  |
+|          |  Appointment Scheduling Software                 |  |  |
+|          |  Apps                 |  |  |
+|          |                  | Mobile Event Apps  |  |
+|          |  Arborist Software                 |  |  |
+|          |  Architectural CAD Software                 |  |  |
+|          |  Architecture Software                 |  |  |
+|          |  Archiving Software                 |  |  |
+|          |  Art Gallery Software                 |  |  |
+|          |  Artificial Intelligence Software                 |  |  |
+|          |  Assessment Software                 |  |  |
+|          |  Asset Tracking Software                 |  |  |
+|          |  Assisted Living Software                 |  |  |
+|          |  Association Management Software                 |  |  |
+|          |  Attendance Tracking Software                 |  |  |
+|          |  Auction Software                 |  |  |
+|          |  Audience Response Software                 |  |  |
+|          |  Audio Conferencing Software                 |  |  |
+|          |  Audio Editing Software                 |  |  |
+|          |  Audit Software                 |  |  |
+|          |  Augmented Reality Software                 |  |  |
+|          |  Authentication Software                 |  |  |
+|          |  Auto Body Software                 |  |  |
+|          |  Auto Dealer Accounting Software                 |  |  |
+|          |  Auto Dealer Software                 |  |  |
+|          |  Auto Dialer Software                 |  |  |
+|          |  Auto Repair Software                 |  |  |
+|          |  Automated Testing Software                 |  |  |
+|          |  Aviation Maintenance Software                 |  |  |
+|          |  BIM Software                 |  |  |
+|          |  Background Check Software                 |  |  |
+|          |  Backup Software                 |  |  |
+|          |  Bakery Software                 |  |  |
+|          |  Banking Systems Software                 |  |  |
+|          |  Bankruptcy Software                 |  |  |
+|          |  Bar POS Software                 |  |  |
+|          |  Barbershop Software                 |  |  |
+|          |  Barcoding Software                 |  |  |
+|          |  Benefits Administration Software                 |  |  |
+|          |  Big Data Software                 |  |  |
+|          |  Billing and Invoicing Software                 |  |  |
+|          |  Billing and Provisioning Software                 |  |  |
+|          |  Blog Software                 |  |  |
+|          |  Board Management Software                 |  |  |
+|          |  Bookkeeper Software                 |  |  |
+|          |  Bot Detection and Mitigation Software                 |  |  |
+|          |  Brand Management Software                 |  |  |
+|          |  Brand Protection Software                 |  |  |
+|          |  Brewery Software                 |  |  |
+|          |  Browser Software                 |  |  |
+|          |  Budgeting Software                 |  |  |
+|          |  Bug Tracking Software                 |  |  |
+|          |  Building Maintenance Software                 |  |  |
+|          |  Business Card Software                 |  |  |
+|          |  Business Continuity Software                 |  |  |
+|          |  Business Intelligence Software                 |  |  |
+|          |  Business Management Software                 |  |  |
+|          |  Business Performance Management Software                 |  |  |
+|          |  Business Phone Systems                 |  |  |
+|          |  Business Plan Software                 |  |  |
+|          |  Business Process Management Software                 |  |  |
+|          |  Buyer Intent Software                 |  |  |
+|          |  CMDB Software                 |  |  |
+|          |  CMMS Software                 |  |  |
+|          |  CMS                 |  |  |
+|          |  CMS Software                 |  |  |
+|          |  CPQ Software                 |  |  |
+|          |  CRM                 |  |  |
+|          |  CRM Software                 |  |  |
+|          |  CTRM Software                 |  |  |
+|          |  Calendar Software                 |  |  |
+|          |  Calibration Management Software                 |  |  |
+|          |  Call Accounting Software                 |  |  |
+|          |  Call Center Software                 |  |  |
+|          |  Call Recording Software                 |  |  |
+|          |  Call Tracking Software                 |  |  |
+|          |  Camp Management Software                 |  |  |
+|          |  Campaign Management Software                 |  |  |
+|          |  Campground Management Software                 |  |  |
+|          |  Car Rental Software                 |  |  |
+|          |  Career Management Software                 |  |  |
+|          |  Carpet Cleaning Software                 |  |  |
+|          |  Catalog Management Software                 |  |  |
+|          |  Catering Software                 |  |  |
+|          |  Cemetery Software                 |  |  |
+|          |  Change Management Software                 |  |  |
+|          |  Channel Management Software                 |  |  |
+|          |  Chatbot Software                 |  |  |
+|          |  Chemical Software                 |  |  |
+|          |  Chiropractic Software                 |  |  |
+|          |  Church Accounting Software                 |  |  |
+|          |  Church Management Software                 |  |  |
+|          |  Church Presentation Software                 |  |  |
+|          |  Claims Processing Software                 |  |  |
+|          |  Class Registration Software                 |  |  |
+|          |  Classroom Management Software                 |  |  |
+|          |  Click Fraud Software                 |  |  |
+|          |  Client Onboarding Software                 |  |  |
+|          |  Clinical Trial Management Software                 |  |  |
+|          |  Closed Captioning Software                 |  |  |
+|          |  Cloud Management Software                 |  |  |
+|          |  Cloud PBX Software                 |  |  |
+|          |  Cloud Security Software                 |  |  |
+|          |  Cloud Storage Software                 |  |  |
+|          |  Club Management Software                 |  |  |
+|          |  Coaching Software                 |  |  |
+|          |  Code Enforcement Software                 |  |  |
+|          |  Collaboration Software                 |  |  |
+|          |  Commercial Insurance Software                 |  |  |
+|          |  Commercial Loan Software                 |  |  |
+|          |  Commercial Real Estate Software                 |  |  |
+|          |  Commission Software                 |  |  |
+|          |  Community Software                 |  |  |
+|          |  Company Secretarial Software                 |  |  |
+|          |  Compensation Management Software                 |  |  |
+|          |  Competitive Intelligence Software                 |  |  |
+|          |  Complaint Management Software                 |  |  |
+|          |  Compliance Software                 |  |  |
+|          |  Computer Repair Shop Software                 |  |  |
+|          |  Computer Security Software                 |  |  |
+|          |  Conference Software                 |  |  |
+|          |  Conflict Checking Software                 |  |  |
+|          |  Consignment Software                 |  |  |
+|          |  Construction Accounting Software                 |  |  |
+|          |  Construction Bid Management Software                 |  |  |
+|          |  Construction CRM Software                 |  |  |
+|          |  Construction Estimating Software                 |  |  |
+|          |  Construction Management Software                 |  |  |
+|          |  Construction Scheduling Software                 |  |  |
+|          |  Contact Center Quality Assurance Software                 |  |  |
+|          |  Contact Center Software                 |  |  |
+|          |  Contact Management Software                 |  |  |
+|          |  Container Security Software                 |  |  |
+|          |  Content Collaboration Software                 |  |  |
+|          |  Content Delivery Network Software                 |  |  |
+|          |  Content Management Software                 |  |  |
+|          |  Content Marketing Software                 |  |  |
+|          |  Contest Software                 |  |  |
+|          |  Continuous Integration Software                 |  |  |
+|          |  Contract Management Software                 |  |  |
+|          |  Contractor Management Software                 |  |  |
+|          |  Convenience Store Software                 |  |  |
+|          |  Corporate Tax Software                 |  |  |
+|          |  Corporate Wellness Software                 |  |  |
+|          |  Corrective and Preventive Action Software                 |  |  |
+|          |  Courier Software                 |  |  |
+|          |  Course Authoring Software                 |  |  |
+|          |  Court Management Software                 |  |  |
+|          |  Creative Management Software                 |  |  |
+|          |  Credentialing Software                 |  |  |
+|          |  Currency Exchange Software                 |  |  |
+|          |  Customer Advocacy Software                 |  |  |
+|          |  Customer Communications Management Software                 |  |  |
+|          |  Customer Engagement Software                 |  |  |
+|          |  Customer Experience Software                 |  |  |
+|          |  Customer Identity and Access Management Software                 |  |  |
+|          |  Customer Loyalty Software                 |  |  |
+|          |  Customer Reference Management Software                 |  |  |
+|          |  Customer Satisfaction Software                 |  |  |
+|          |  Customer Service Software                 |  |  |
+|          |  Customer Success Software                 |  |  |
+|          |  Customer Support Software                 |  |  |
+|          |  Cybersecurity Software                 |  |  |
+|          |  DDoS Protection Software                 |  |  |
+|          |  Dance Studio Software                 |  |  |
+|          |  Dashboard Software                 |  |  |
+|          |  Data Analysis Software                 |  |  |
+|          |  Data Center Management Software                 |  |  |
+|          |  Data Discovery Software                 |  |  |
+|          |  Data Entry Software                 |  |  |
+|          |  Data Extraction Software                 |  |  |
+|          |  Data Governance Software                 |  |  |
+|          |  Data Loss Prevention Software                 |  |  |
+|          |  Data Management Software                 |  |  |
+|          |  Data Mining Software                 |  |  |
+|          |  Data Preparation Software                 |  |  |
+|          |  Data Quality Software                 |  |  |
+|          |  Data Visualization Software                 |  |  |
+|          |  Data Warehouse Software                 |  |  |
+|          |  Database Monitoring Software                 |  |  |
+|          |  Database Software                 |  |  |
+|          |  Databases                 |  |  |
+|          |  Daycare Software                 |  |  |
+|          |  Debt Collection Software                 |  |  |
+|          |  Decision Support Software                 |  |  |
+|          |  Deep Learning Software                 |  |  |
+|          |  Delivery Management Software                 |  |  |
+|          |  Demand Planning Software                 |  |  |
+|          |  Demand Side Platform Software                 |  |  |
+|          |  Dental Charting Software                 |  |  |
+|          |  Dental Imaging Software                 |  |  |
+|          |  Dental Software                 |  |  |
+|          |  Dermatology Software                 |  |  |
+|          |  Desk Booking Software                 |  |  |
+|          |  Desktop as a Service Software                 |  |  |
+|          |  DevOps Software                 |  |  |
+|          |  Diagram Software                 |  |  |
+|          |  Digital Asset Management Software                 |  |  |
+|          |  Digital Experience Platforms Software                 |  |  |
+|          |  Digital Forensics Software                 |  |  |
+|          |  Digital Rights Management Software                 |  |  |
+|          |  Digital Signage Software                 |  |  |
+|          |  Digital Signature Software                 |  |  |
+|          |  Digital Workplace Software                 |  |  |
+|          |  Direct Mail Automation Software                 |  |  |
+|          |  Directory Software                 |  |  |
+|          |  Disk Imaging Software                 |  |  |
+|          |  Display Advertising Software                 |  |  |
+|          |  Distribution Software                 |  |  |
+|          |  Dock Scheduling Software                 |  |  |
+|          |  Docketing Software                 |  |  |
+|          |  Document Control Software                 |  |  |
+|          |  Document Generation Software                 |  |  |
+|          |  Document Management Software                 |  |  |
+|          |  Document Version Control Software                 |  |  |
+|          |  Donation Management Software                 |  |  |
+|          |  Driving School Software                 |  |  |
+|          |  Dropshipping Software                 |  |  |
+|          |  Dry Cleaning Software                 |  |  |
+|          |  EAM Software                 |  |  |
+|          |  EDI Software                 |  |  |
+|          |  EHS Management Software                 |  |  |
+|          |  EMS Software                 |  |  |
+|          |  ERP Software                 |  |  |
+|          |  ESG Software                 |  |  |
+|          |  ETL Software                 |  |  |
+|          |  Ecommerce                 |  |  |
+|          |  Electrical Contractor Software                 |  |  |
+|          |  Electrical Design Software                 |  |  |
+|          |  Electrical Estimating Software                 |  |  |
+|          |  Electronic Data Capture Software                 |  |  |
+|          |  Electronic Discovery Software                 |  |  |
+|          |  Electronic Lab Notebook Software                 |  |  |
+|          |  Electronic Medical Records Software                 |  |  |
+|          |  Email Archiving Software                 |  |  |
+|          |  Email Management Software                 |  |  |
+|          |  Email Marketing Software                 |  |  |
+|          |  Email Security Software                 |  |  |
+|          |  Email Signature Software                 |  |  |
+|          |  Email Tracking Software                 |  |  |
+|          |  Embedded Analytics Software                 |  |  |
+|          |  Emergency Notification Software                 |  |  |
+|          |  Emissions Management Software                 |  |  |
+|          |  Employee Advocacy Software                 |  |  |
+|          |  Employee Engagement Software                 |  |  |
+|          |  Employee Monitoring Software                 |  |  |
+|          |  Employee Recognition Software                 |  |  |
+|          |  Employee Scheduling Software                 |  |  |
+|          |  Encryption Software                 |  |  |
+|          |  Endpoint Detection and Response Software                 |  |  |
+|          |  Endpoint Protection Software                 |  |  |
+|          |  Energy Management Software                 |  |  |
+|          |  Engineering CAD Software                 |  |  |
+|          |  Enterprise Architecture Software                 |  |  |
+|          |  Enterprise Content Management Software                 |  |  |
+|          |  Enterprise Legal Management Software                 |  |  |
+|          |  Enterprise Resource Planning                 |  |  |
+|          |  Enterprise Search Software                 |  |  |
+|          |  Enterprise Service Bus Software                 |  |  |
+|          |  Entity Management Software                 |  |  |
+|          |  Environmental Software                 |  |  |
+|          |  Equipment Maintenance Software                 |  |  |
+|          |  Equipment Rental Software                 |  |  |
+|          |  Equity Management Software                 |  |  |
+|          |  Event Booking Software                 |  |  |
+|          |  Event Check In Software                 |  |  |
+|          |  Event Management Software                 |  |  |
+|          |  Event Marketing Software                 |  |  |
+|          |  Event Rental Software                 |  |  |
+|          |  Exam Software                 |  |  |
+|          |  Expense Report Software                 |  |  |
+|          |  Facility Management Software                 |  |  |
+|          |  Farm Management Software                 |  |  |
+|          |  Fashion Design Software                 |  |  |
+|          |  Fax Server Software                 |  |  |
+|          |  Festival Management Software                 |  |  |
+|          |  Field Sales Software                 |  |  |
+|          |  Field Service Management Software                 |  |  |
+|          |  File Sharing Software                 |  |  |
+|          |  File Sync Software                 |  |  |
+|          |  Financial CRM Software                 |  |  |
+|          |  Financial Close Software                 |  |  |
+|          |  Financial Fraud Detection Software                 |  |  |
+|          |  Financial Management Software                 |  |  |
+|          |  Financial Reporting Software                 |  |  |
+|          |  Financial Risk Management Software                 |  |  |
+|          |  Financial Services Software                 |  |  |
+|          |  Fire Department Software                 |  |  |
+|          |  Firewall Software                 |  |  |
+|          |  Fitness Software                 |  |  |
+|          |  Fixed Asset Management Software                 |  |  |
+|          |  Fleet Maintenance Software                 |  |  |
+|          |  Fleet Management Software                 |  |  |
+|          |  Florist Software                 |  |  |
+|          |  Flowchart Software                 |  |  |
+|          |  Food Costing Software                 |  |  |
+|          |  Food Delivery Software                 |  |  |
+|          |  Food Service Distribution Software                 |  |  |
+|          |  Food Service Management Software                 |  |  |
+|          |  Food Traceability Software                 |  |  |
+|          |  Forestry Software                 |  |  |
+|          |  Form Builder Software                 |  |  |
+|          |  Forms Automation Software                 |  |  |
+|          |  Franchise Management Software                 |  |  |
+|          |  Freight Software                 |  |  |
+|          |  Fuel Management Software                 |  |  |
+|          |  Fund Accounting Software                 |  |  |
+|          |  Fundraising Software                 |  |  |
+|          |  Funeral Home Software                 |  |  |
+|          |  GDPR Compliance Software                 |  |  |
+|          |  GIS Software                 |  |  |
+|          |  GPS Tracking Software                 |  |  |
+|          |  Game Development Software                 |  |  |
+|          |  Gamification Software                 |  |  |
+|          |  Gantt Chart Software                 |  |  |
+|          |  Garage Door Software                 |  |  |
+|          |  Garden Center Software                 |  |  |
+|          |  Golf Course Software                 |  |  |
+|          |  Governance Risk And Compliance Software                 |  |  |
+|          |  Government Software                 |  |  |
+|          |  Gradebook Software                 |  |  |
+|          |  Grant Management Software                 |  |  |
+|          |  Graphic Design Software                 |  |  |
+|          |  Gym Management Software                 |  |  |
+|          |  Gymnastics Software                 |  |  |
+|          |  HIPAA Compliance Software                 |  |  |
+|          |  HOA Software                 |  |  |
+|          |  HR Analytics Software                 |  |  |
+|          |  HVAC Estimating Software                 |  |  |
+|          |  HVAC Software                 |  |  |
+|          |  Handyman Software                 |  |  |
+|          |  Headless CMS Software                 |  |  |
+|          |  Headless eCommerce Software                 |  |  |
+|          |  Healthcare CRM Software                 |  |  |
+|          |  Heatmap Software                 |  |  |
+|          |  Hedge Fund Software                 |  |  |
+|          |  Help Desk Software                 |  |  |
+|          |  Higher Education Software                 |  |  |
+|          |  Home Builder Software                 |  |  |
+|          |  Home Care Software                 |  |  |
+|          |  Home Health Care Software                 |  |  |
+|          |  Home Inspection Software                 |  |  |
+|          |  Horse Software                 |  |  |
+|          |  Hospice Software                 |  |  |
+|          |  Hospital Management Software                 |  |  |
+|          |  Hospitality Property Management Software                 |  |  |
+|          |  Hostel Management Software                 |  |  |
+|          |  Hotel Channel Management Software                 |  |  |
+|          |  Human Resources Software                 |  |  |
+|          |  Human Services Software                 |  |  |
+|          |  Hybrid Events Software                 |  |  |
+|          |  IT Asset Management Software                 |  |  |
+|          |  IT Management Software                 |  |  |
+|          |  IT Project Management Software                 |  |  |
+|          |  IT Service Software                 |  |  |
+|          |  ITSM Software                 |  |  |
+|          |  IVR Software                 |  |  |
+|          |  IWMS Software                 |  |  |
+|          |  Idea Management Software                 |  |  |
+|          |  Identity Management Software                 |  |  |
+|          |  Incident Management Software                 |  |  |
+|          |  Influencer Marketing Software                 |  |  |
+|          |  Innovation Software                 |  |  |
+|          |  Inside Sales Software                 |  |  |
+|          |  Insight Engines Software                 |  |  |
+|          |  Inspection Software                 |  |  |
+|          |  Insurance Policy Software                 |  |  |
+|          |  Insurance Rating Software                 |  |  |
+|          |  Insurance Software                 |  |  |
+|          |  Integrated Development Environment Software                 |  |  |
+|          |  Integrated Risk Management Software                 |  |  |
+|          |  Integration Software                 |  |  |
+|          |  Intellectual Property Management Software                 |  |  |
+|          |  Internal Communications Software                 |  |  |
+|          |  Intranet Software                 |  |  |
+|          |  Inventory Control Software                 |  |  |
+|          |  Inventory Management Software                 |  |  |
+|          |  Investigation Management Software                 |  |  |
+|          |  Investment Management Software                 |  |  |
+|          |  IoT Analytics Software                 |  |  |
+|          |  IoT Software                 |  |  |
+|          |  Issue Tracking Software                 |  |  |
+|          |  Jail Management Software                 |  |  |
+|          |  Janitorial Software                 |  |  |
+|          |  Java CMS Software                 |  |  |
+|          |  JavaScript Frameworks                 |  |  |
+|          |  Jewelry Store Management Software                 |  |  |
+|          |  Job Board Software                 |  |  |
+|          |  Job Costing Software                 |  |  |
+|          |  Job Evaluation Software                 |  |  |
+|          |  Job Shop Software                 |  |  |
+|          |  K12 Software                 |  |  |
+|          |  Kennel Software                 |  |  |
+|          |  Key Management Software                 |  |  |
+|          |  Kiosk Software                 |  |  |
+|          |  Knowledge Base Software                 |  |  |
+|          |  Knowledge Management Software                 |  |  |
+|          |  LMS Software                 |  |  |
+|          |  Label Printing Software                 |  |  |
+|          |  Laboratory Information Management System Software                 |  |  |
+|          |  Land Management Software                 |  |  |
+|          |  Landing Page Software                 |  |  |
+|          |  Landscape Software                 |  |  |
+|          |  Language Learning Software                 |  |  |
+|          |  Law Enforcement Software                 |  |  |
+|          |  Law Practice Management Software                 |  |  |
+|          |  Lawn Care Software                 |  |  |
+|          |  Lead Capture Software                 |  |  |
+|          |  Lead Generation Software                 |  |  |
+|          |  Lead Management Software                 |  |  |
+|          |  Lead Nurturing Software                 |  |  |
+|          |  Learning Experience Platform Software                 |  |  |
+|          |  Learning Management System                 |  |  |
+|          |  Lease Accounting Software                 |  |  |
+|          |  Lease Management Software                 |  |  |
+|          |  Leave Management System                 |  |  |
+|          |  Legal Billing Software                 |  |  |
+|          |  Legal Calendar Software                 |  |  |
+|          |  Legal Case Management Software                 |  |  |
+|          |  Legal Document Management Software                 |  |  |
+|          |  Legal Research Software                 |  |  |
+|          |  Library Automation Software                 |  |  |
+|          |  License Management Software                 |  |  |
+|          |  Live Chat Software                 |  |  |
+|          |  Live Streaming Software                 |  |  |
+|          |  Load Balancing Software                 |  |  |
+|          |  Load Testing Software                 |  |  |
+|          |  Loan Origination Software                 |  |  |
+|          |  Loan Servicing Software                 |  |  |
+|          |  Location Intelligence Software                 |  |  |
+|          |  Locksmith Software                 |  |  |
+|          |  Log Analysis Software                 |  |  |
+|          |  Log Management Software                 |  |  |
+|          |  Logbook Software                 |  |  |
+|          |  Logistics Software                 |  |  |
+|          |  Long Term Care Software                 |  |  |
+|          |  Lost and Found Software                 |  |  |
+|          |  MLM Software                 |  |  |
+|          |  MRM Software                 |  |  |
+|          |  MRP Software                 |  |  |
+|          |  Mac CRM Software                 |  |  |
+|          |  Machine Learning Software                 |  |  |
+|          |  Maid Service Software                 |  |  |
+|          |  Mailroom Management Software                 |  |  |
+|          |  Maintenance Management Software                 |  |  |
+|          |  Managed Service Providers Software                 |  |  |
+|          |  Manufacturing Execution Software                 |  |  |
+|          |  Manufacturing Software                 |  |  |
+|          |  Marine Software                 |  |  |
+|          |  Market Research Software                 |  |  |
+|          |  Marketing Analytics Software                 |  |  |
+|          |  Marketing Attribution Software                 |  |  |
+|          |  Marketing Automation                 |  |  |
+|          |  Marketing Automation Software                 |  |  |
+|          |  Marketing Planning Software                 |  |  |
+|          |  Marketplace Software                 |  |  |
+|          |  Martial Arts Software                 |  |  |
+|          |  Massage Therapy Software                 |  |  |
+|          |  Master Data Management Software                 |  |  |
+|          |  Medical Billing Software                 |  |  |
+|          |  Medical Imaging Software                 |  |  |
+|          |  Medical Inventory Software                 |  |  |
+|          |  Medical Lab Software                 |  |  |
+|          |  Medical Practice Management Software                 |  |  |
+|          |  Medical Scheduling Software                 |  |  |
+|          |  Medical Spa Software                 |  |  |
+|          |  Medical Transcription Software                 |  |  |
+|          |  Meeting Room Booking System                 |  |  |
+|          |  Meeting Software                 |  |  |
+|          |  Membership Management Software                 |  |  |
+|          |  Mental Health Software                 |  |  |
+|          |  Mentoring Software                 |  |  |
+|          |  Metadata Management Software                 |  |  |
+|          |  Microlearning Software                 |  |  |
+|          |  Mind Mapping Software                 |  |  |
+|          |  Mining Software                 |  |  |
+|          |  Mobile Analytics Software                 |  |  |
+|          |  Mobile Banking Software                 |  |  |
+|          |  Mobile Content Management System                 |  |  |
+|          |  Mobile Credit Card Processing Software                 |  |  |
+|          |  Mobile Device Management Software                 |  |  |
+|          |  Mobile Frameworks                 |  |  |
+|          |  Mobile Learning Software                 |  |  |
+|          |  Mobile Marketing Software                 |  |  |
+|          |  Mobility Software                 |  |  |
+|          |  Mortgage Software                 |  |  |
+|          |  Moving Software                 |  |  |
+|          |  MultiChannel eCommerce Software                 |  |  |
+|          |  MultiFactor Authentication Software                 |  |  |
+|          |  Municipal Software                 |  |  |
+|          |  Museum Software                 |  |  |
+|          |  Music School Software                 |  |  |
+|          |  NPS Software                 |  |  |
+|          |  Natural Language Processing Software                 |  |  |
+|          |  Network Access Control Software                 |  |  |
+|          |  Network Management Software                 |  |  |
+|          |  Network Mapping Software                 |  |  |
+|          |  Network Monitoring Software                 |  |  |
+|          |  Network Security Software                 |  |  |
+|          |  Network Troubleshooting Software                 |  |  |
+|          |  No Code Platform Software                 |  |  |
+|          |  NoSQL Databases                 |  |  |
+|          |  Nonprofit Accounting Software                 |  |  |
+|          |  Nonprofit CRM Software                 |  |  |
+|          |  Nonprofit Project Management Software                 |  |  |
+|          |  Nonprofit Software                 |  |  |
+|          |  NoteTaking Software                 |  |  |
+|          |  Nurse Scheduling Software                 |  |  |
+|          |  Nursing Home Software                 |  |  |
+|          |  Nutrition Analysis Software                 |  |  |
+|          |  Nutritionist Software                 |  |  |
+|          |  OCR Software                 |  |  |
+|          |  OEE Software                 |  |  |
+|          |  OKR Software                 |  |  |
+|          |  Occupational Therapy Software                 |  |  |
+|          |  Oil and Gas Software                 |  |  |
+|          |  Onboarding Software                 |  |  |
+|          |  Online Banking Software                 |  |  |
+|          |  Online CRM Software                 |  |  |
+|          |  Online Ordering Software                 |  |  |
+|          |  Online Proofing Software                 |  |  |
+|          |  Operating Systems                 |  |  |
+|          |  Optometry Software                 |  |  |
+|          |  Order Entry Software                 |  |  |
+|          |  Order Management Software                 |  |  |
+|          |  Org Chart Software                 |  |  |
+|          |  PACS Software                 |  |  |
+|          |  PAndC Insurance Software                 |  |  |
+|          |  PCI Compliance Software                 |  |  |
+|          |  PDF Editor Software                 |  |  |
+|          |  PDF Software                 |  |  |
+|          |  PIM Software                 |  |  |
+|          |  PPC Software                 |  |  |
+|          |  Packaging Software                 |  |  |
+|          |  Parcel Audit Software                 |  |  |
+|          |  Parking Management Software                 |  |  |
+|          |  Parks and Recreation Software                 |  |  |
+|          |  Partner Management Software                 |  |  |
+|          |  Password Management Software                 |  |  |
+|          |  Patch Management Software                 |  |  |
+|          |  Patient Case Management Software                 |  |  |
+|          |  Patient Engagement Software                 |  |  |
+|          |  Patient Management Software                 |  |  |
+|          |  Patient Portal Software                 |  |  |
+|          |  Patient Scheduling Software                 |  |  |
+|          |  Pawn Shop Software                 |  |  |
+|          |  Payment Processing Software                 |  |  |
+|          |  Payroll Software                 |  |  |
+|          |  Pediatric Software                 |  |  |
+|          |  Performance Management System Software                 |  |  |
+|          |  Performance Testing Software                 |  |  |
+|          |  Permit Software                 |  |  |
+|          |  Personal Trainer Software                 |  |  |
+|          |  Personalization Software                 |  |  |
+|          |  Pest Control Software                 |  |  |
+|          |  Pet Grooming Software                 |  |  |
+|          |  Pet Sitting Software                 |  |  |
+|          |  Pharmacy Software                 |  |  |
+|          |  Photo Editing Software                 |  |  |
+|          |  Photography Studio Software                 |  |  |
+|          |  Physical Security Software                 |  |  |
+|          |  Physical Therapy Software                 |  |  |
+|          |  Pilates Studio Software                 |  |  |
+|          |  Plagiarism Checker                 |  |  |
+|          |  Plastic Surgery Software                 |  |  |
+|          |  Platform                 |  |  |
+|          |                  | AllinOne Marketing Platform  |  |
+|          |                  | B2B eCommerce Platform  |  |
+|          |                  | Blockchain Platform  |  |
+|          |                  | Cloud Communication Platform  |  |
+|          |                  | Conversational AI Platform  |  |
+|          |                  | Conversational Marketing Platform  |  |
+|          |                  | Customer Data Platform  |  |
+|          |                  | Data Management Platform  |  |
+|          |                  | Digital Adoption Platform  |  |
+|          |                  | Low Code Development Platform  |  |
+|          |                  | Open SMS Platform  |  |
+|          |                  | Recruitment Marketing Platform  |  |
+|          |                  | Student Engagement Platform  |  |
+|          |  Plumbing Estimating Software                 |  |  |
+|          |  Plumbing Software                 |  |  |
+|          |  Podcast Hosting Software                 |  |  |
+|          |  Podiatry Software                 |  |  |
+|          |  Point of Sale Software                 |  |  |
+|          |  Policy Management Software                 |  |  |
+|          |  Political Campaign Software                 |  |  |
+|          |  Polling Software                 |  |  |
+|          |  Pool Service Software                 |  |  |
+|          |  Portal Software                 |  |  |
+|          |  Predictive Analytics Software                 |  |  |
+|          |  Predictive Dialer Software                 |  |  |
+|          |  Predictive Lead Scoring Software                 |  |  |
+|          |  Preemployment Testing Software                 |  |  |
+|          |  Presentation Software                 |  |  |
+|          |  Preventive Maintenance Software                 |  |  |
+|          |  Pricing Optimization Software                 |  |  |
+|          |  Print Estimating Software                 |  |  |
+|          |  Print Management Software                 |  |  |
+|          |  Privileged Access Management Software                 |  |  |
+|          |  Proctoring Software                 |  |  |
+|          |  Procure to Pay Software                 |  |  |
+|          |  Procurement Software                 |  |  |
+|          |  Product Analytics Software                 |  |  |
+|          |  Product Configurator Software                 |  |  |
+|          |  Product Data Management Software                 |  |  |
+|          |  Product Lifecycle Management Software                 |  |  |
+|          |  Product Management Software                 |  |  |
+|          |  Product Roadmap Software                 |  |  |
+|          |  Production Scheduling Software                 |  |  |
+|          |  Productivity Software                 |  |  |
+|          |  Professional Services Automation Software                 |  |  |
+|          |  Programming Languages                 |  |  |
+|          |  Project Management Software                 |  |  |
+|          |  Project Planning Software                 |  |  |
+|          |  Project Portfolio Management Software                 |  |  |
+|          |  Project Tracking Software                 |  |  |
+|          |  Proofreading Software                 |  |  |
+|          |  Property Management Software                 |  |  |
+|          |  Proposal Management Software                 |  |  |
+|          |  Prototyping Software                 |  |  |
+|          |  Public Relations Software                 |  |  |
+|          |  Public Transportation Software                 |  |  |
+|          |  Public Works Software                 |  |  |
+|          |  Publishing and Subscriptions Software                 |  |  |
+|          |  Punch List Software                 |  |  |
+|          |  Purchasing Software                 |  |  |
+|          |  Push Notifications Software                 |  |  |
+|          |  Qualitative Data Analysis Software                 |  |  |
+|          |  Quality Management Software                 |  |  |
+|          |  Quoting Software                 |  |  |
+|          |  RDBMS Software                 |  |  |
+|          |  RFP Software                 |  |  |
+|          |  Radiology Software                 |  |  |
+|          |  Real Estate Accounting Software                 |  |  |
+|          |  Real Estate Agency Software                 |  |  |
+|          |  Real Estate CMA Software                 |  |  |
+|          |  Real Estate CRM Software                 |  |  |
+|          |  Real Estate Property Management Software                 |  |  |
+|          |  Real Estate Transaction Management Software                 |  |  |
+|          |  Recruiting Agency Software                 |  |  |
+|          |  Recruiting Software                 |  |  |
+|          |  Recurring Billing Software                 |  |  |
+|          |  Recycling Software                 |  |  |
+|          |  Reference Check Software                 |  |  |
+|          |  Referral Software                 |  |  |
+|          |  Registration Software                 |  |  |
+|          |  Relocation Software                 |  |  |
+|          |  Remodeling Estimating Software                 |  |  |
+|          |  Remote Desktop Software                 |  |  |
+|          |  Remote Monitoring and Management Software                 |  |  |
+|          |  Remote Patient Monitoring Software                 |  |  |
+|          |  Remote Support Software                 |  |  |
+|          |  Remote Work Software                 |  |  |
+|          |  Rental Software                 |  |  |
+|          |  Reputation Management Software                 |  |  |
+|          |  Requirements Management Software                 |  |  |
+|          |  Reservations Software                 |  |  |
+|          |  Residential Construction Estimating Software                 |  |  |
+|          |  Resource Management Software                 |  |  |
+|          |  Restaurant Management Software                 |  |  |
+|          |  Restaurant POS Software                 |  |  |
+|          |  Retail Management Systems Software                 |  |  |
+|          |  Retail POS System                 |  |  |
+|          |  Retargeting Software                 |  |  |
+|          |  Revenue Cycle Management Software                 |  |  |
+|          |  Revenue Management Software                 |  |  |
+|          |  Review Management Software                 |  |  |
+|          |  Risk Management Software                 |  |  |
+|          |  Robotic Process Automation                 |  |  |
+|          |  Roofing Software                 |  |  |
+|          |  Route Planning Software                 |  |  |
+|          |  SCADA Software                 |  |  |
+|          |  SEO Software                 |  |  |
+|          |  SIEM Software                 |  |  |
+|          |  SMS Marketing Software                 |  |  |
+|          |  SMS Survey Software                 |  |  |
+|          |  SOAR Software                 |  |  |
+|          |  SPC Software                 |  |  |
+|          |  SaaS Management Software                 |  |  |
+|          |  Safety Management Software                 |  |  |
+|          |  Sales Coaching Software                 |  |  |
+|          |  Sales Content Management Software                 |  |  |
+|          |  Sales Enablement Software                 |  |  |
+|          |  Sales Engagement Platform Software                 |  |  |
+|          |  Sales Force Automation Software                 |  |  |
+|          |  Sales Forecasting Software                 |  |  |
+|          |  Sales Performance Management Software                 |  |  |
+|          |  Sales Tax Software                 |  |  |
+|          |  Sales Tracking Software                 |  |  |
+|          |  Salon Software                 |  |  |
+|          |  Scheduling Software                 |  |  |
+|          |  Scholarship Management Software                 |  |  |
+|          |  School Accounting Software                 |  |  |
+|          |  School Bus Routing Software                 |  |  |
+|          |  School Management Software                 |  |  |
+|          |  Screen Recording Software                 |  |  |
+|          |  Screen Sharing Software                 |  |  |
+|          |  Scrum Software                 |  |  |
+|          |  Secure Email Gateway Software                 |  |  |
+|          |  Security Awareness Training Software                 |  |  |
+|          |  Security Information Management                 |  |  |
+|          |  Security Orchestration Automation and Response Software                 |  |  |
+|          |  Security System Installer Software                 |  |  |
+|          |  Self Storage Software                 |  |  |
+|          |  SelfService Password Reset Software                 |  |  |
+|          |  Server Backup Software                 |  |  |
+|          |  Server Management Software                 |  |  |
+|          |  Server Monitoring Software                 |  |  |
+|          |  Service Desk Software                 |  |  |
+|          |  Service Dispatch Software                 |  |  |
+|          |  Shipment Tracking Software                 |  |  |
+|          |  Shipping Software                 |  |  |
+|          |  Shopping Cart Software                 |  |  |
+|          |  Simulation Software                 |  |  |
+|          |  Single Sign On Software                 |  |  |
+|          |  Small Business CRM Software                 |  |  |
+|          |  Small Business Loyalty Programs Software                 |  |  |
+|          |  Small Business eCommerce Software                 |  |  |
+|          |  Social Media Management Software                 |  |  |
+|          |  Social Media Marketing Software                 |  |  |
+|          |  Social Media Monitoring Software                 |  |  |
+|          |  Social Networking Software                 |  |  |
+|          |  Social Selling Software                 |  |  |
+|          |  Social Work Case Management Software                 |  |  |
+|          |  Softphone Software                 |  |  |
+|          |  Software Tools                 |  |  |
+|          |                  | Agile Project Management Tools  |  |
+|          |                  | App Store Optimization Tools  |  |
+|          |                  | Configuration Management Tools  |  |
+|          |                  | Customer Journey Mapping Tools  |  |
+|          |                  | Email Verification Tools  |  |
+|          |                  | Employee Communication Tools  |  |
+|          |                  | Kanban Tools  |  |
+|          |                  | Link Management Tools  |  |
+|          |                  | Reporting Tools  |  |
+|          |                  | Social CRM Tools  |  |
+|          |                  | Social Listening Tools  |  |
+|          |                  | Social Media Analytics Tools  |  |
+|          |                  | Website Optimization Tools  |  |
+|          |                  | eLearning Authoring Tools  |  |
+|          |  Solutions                 |  |  |
+|          |                  | Infrastructure as a Service Solutions  |  |
+|          |                  | Platform as a Service Solutions  |  |
+|          |  Source Code Management Software                 |  |  |
+|          |  Sourcing Software                 |  |  |
+|          |  Spa Software                 |  |  |
+|          |  Space Management Software                 |  |  |
+|          |  Speech Analytics Software                 |  |  |
+|          |  Speech Recognition Software                 |  |  |
+|          |  Speech Therapy Software                 |  |  |
+|          |  Spend Management Software                 |  |  |
+|          |  Sports League Software                 |  |  |
+|          |  Spreadsheet Software                 |  |  |
+|          |  Staffing Agency Software                 |  |  |
+|          |  Static Application Security Testing Software                 |  |  |
+|          |  Statistical Analysis Software                 |  |  |
+|          |  Stock Portfolio Management Software                 |  |  |
+|          |  Store Locator Software                 |  |  |
+|          |  Strategic Planning Software                 |  |  |
+|          |  Student Information System Software                 |  |  |
+|          |  Subscription Management Software                 |  |  |
+|          |  Succession Planning Software                 |  |  |
+|          |  Supply Chain Management Software                 |  |  |
+|          |  Survey Software                 |  |  |
+|          |  Sustainability Software                 |  |  |
+|          |  Swim School Software                 |  |  |
+|          |  Takeoff Software                 |  |  |
+|          |  Talent Management Software                 |  |  |
+|          |  Task Management Software                 |  |  |
+|          |  Tattoo Studio Software                 |  |  |
+|          |  Tax Practice Management Software                 |  |  |
+|          |  Team Communication Software                 |  |  |
+|          |  Team Management Software                 |  |  |
+|          |  Telecom Expense Management Software                 |  |  |
+|          |  Telemarketing Software                 |  |  |
+|          |  Telemedicine Software                 |  |  |
+|          |  Telephony Software                 |  |  |
+|          |  Text Mining Software                 |  |  |
+|          |  TextToSpeech Software                 |  |  |
+|          |  Threat Intelligence Software                 |  |  |
+|          |  ThreeD Architecture Software                 |  |  |
+|          |  ThreeD CAD Software                 |  |  |
+|          |  ThreeSixty Degree Feedback Software                 |  |  |
+|          |  Ticketing Software                 |  |  |
+|          |  Time Clock Software                 |  |  |
+|          |  Time Tracking Software                 |  |  |
+|          |  Time and Expense Software                 |  |  |
+|          |  Timeshare Software                 |  |  |
+|          |  Tool Management Software                 |  |  |
+|          |  Tour Operator Software                 |  |  |
+|          |  Towing Software                 |  |  |
+|          |  Trade Promotion Management Software                 |  |  |
+|          |  Training Software                 |  |  |
+|          |  Transactional Email Software                 |  |  |
+|          |  Transcription Software                 |  |  |
+|          |  Translation Management Software                 |  |  |
+|          |  Transportation Dispatch Software                 |  |  |
+|          |  Transportation Management Software                 |  |  |
+|          |  Travel Agency Software                 |  |  |
+|          |  Travel Management Software                 |  |  |
+|          |  Treasury Software                 |  |  |
+|          |  Trucking Software                 |  |  |
+|          |  Trust Accounting Software                 |  |  |
+|          |  Tutoring Software                 |  |  |
+|          |  UI Frameworks                 |  |  |
+|          |  URL Shortener                 |  |  |
+|          |  UX Software                 |  |  |
+|          |  Unified Communications Software                 |  |  |
+|          |  Unified Endpoint Management Software                 |  |  |
+|          |  User Testing Software                 |  |  |
+|          |  Utility Billing Software                 |  |  |
+|          |  Utility Management Systems Software                 |  |  |
+|          |  VDI Software                 |  |  |
+|          |  VPN Software                 |  |  |
+|          |  Vacation Rental Software                 |  |  |
+|          |  Vaccine Management Software                 |  |  |
+|          |  Vector Graphics Software                 |  |  |
+|          |  Vendor Management Software                 |  |  |
+|          |  Venue Management Software                 |  |  |
+|          |  Veterinary Software                 |  |  |
+|          |  Video Conferencing Software                 |  |  |
+|          |  Video Editing Software                 |  |  |
+|          |  Video Hosting Software                 |  |  |
+|          |  Video Interviewing Software                 |  |  |
+|          |  Video Making Software                 |  |  |
+|          |  Video Management Software                 |  |  |
+|          |  Video Marketing Software                 |  |  |
+|          |  Virtual Classroom Software                 |  |  |
+|          |  Virtual Data Room Software                 |  |  |
+|          |  Virtual Event Software                 |  |  |
+|          |  Virtual Machine Software                 |  |  |
+|          |  Virtual Private Server Software                 |  |  |
+|          |  Virtual Reality Software                 |  |  |
+|          |  Virtual Tour Software                 |  |  |
+|          |  Virtualization Software                 |  |  |
+|          |  Visitor Management Software                 |  |  |
+|          |  Visual Search Software                 |  |  |
+|          |  VoIP Software                 |  |  |
+|          |  Volunteer Management Software                 |  |  |
+|          |  Voting Software                 |  |  |
+|          |  Vulnerability Management Software                 |  |  |
+|          |  Vulnerability Scanner Software                 |  |  |
+|          |  Waitlist Software                 |  |  |
+|          |  Waiver Software                 |  |  |
+|          |  Wallets                 |  |  |
+|          |                  | Cryptocurrency Wallets  |  |
+|          |  Warehouse Management Software                 |  |  |
+|          |  Warranty Management Software                 |  |  |
+|          |  Waste Management Software                 |  |  |
+|          |  Web Analytics Software                 |  |  |
+|          |  Web Conferencing Software                 |  |  |
+|          |  Web Content Management Software                 |  |  |
+|          |  Web Frameworks                 |  |  |
+|          |  Web to Print Software                 |  |  |
+|          |  Webinar Software                 |  |  |
+|          |  Website Accessibility Software                 |  |  |
+|          |  Website Builder Software                 |  |  |
+|          |  Website Monitoring Software                 |  |  |
+|          |  Website Security Software                 |  |  |
+|          |  Whistleblowing Software                 |  |  |
+|          |  Whiteboard Software                 |  |  |
+|          |  Winery Software                 |  |  |
+|          |  Wireframe Software                 |  |  |
+|          |  Wireless Expense Management Software                 |  |  |
+|          |  Work Order Software                 |  |  |
+|          |  Workflow Management Software                 |  |  |
+|          |  Workforce Management Software                 |  |  |
+|          |  Worship Software                 |  |  |
+|          |  Yard Management Software                 |  |  |
+|          |  Yoga Studio Software                 |  |  |
+|          |  Zoo Software                 |  |  |
+|          |  eCommerce Software                 |  |  |
+|          |  eDiscovery Software                 |  |  |
+|          |  ePrescribing Software                 |  |  |
+|          |  iPaaS Software                 |  |  |
+|          |  iPad Kiosk Software                 |  |  |
+|          |  iPad POS Software                 |  |  |
+|  Sound technology         |                   |   |  |
+|  Sports technology         |                   |   |  |
+|  Supply chain and logistics         |                   |   |  |
+|  ThreeD printing processes         |                   |   |  |
+|  Tools         |                   |   |  |
+|  Travel technology         |                   |   |  |
+|  Trenchless technology         |                   |   |  |
+|  Vehicle technology         |                   |   |  |
+|  Vehicles by type         |                   |   |  |
+|  Waste treatment technology         |                   |   |  |
+|  Water technology         |                   |   |  |
+|  Web technology         |                   |   |  |
+
+
+<style>
+/* Hides the Right-Hand Secondary Nav for a Full Width Industry Table */
+.onPageNav {
+    display: none;
+}
+/* Hides the Unnecessary Prev/Next Buttons for this Reference Doc */
+.docs-prevnext {
+    display: none;
+}
+</style>
\ No newline at end of file
diff --git a/docs/nl-index.md b/docs/nl-index.md
index daec70db..4510c465 100644
--- a/docs/nl-index.md
+++ b/docs/nl-index.md
@@ -25,7 +25,7 @@ The Natural Language API allows developers to extract entities (e.g., people, or
 
 ## Supported Languages
  * Sentiment: Over a 100 languages.
- * Entities and salience: English (en), French (fr), Spanish (es), Chinese (zh), German (de), Russian (ru), Japanese (ja), Dutch (nl), Polish (pl), Norwegian (no), Danish (da), Swedish (sv)
+ * Entities and salience: English (en), French (fr), Spanish (es), Chinese (zh), German (de), Russian (ru), Japanese (ja), Dutch (nl), Polish (pl), Norwegian (no), Danish (da), Swedish (sv), Italian (it)
  * Other fields: English (en) only.
 
 ## Credits
diff --git a/website/generateIndustries.js b/website/generateIndustries.js
index 00a39b25..f2577933 100644
--- a/website/generateIndustries.js
+++ b/website/generateIndustries.js
@@ -10,8 +10,8 @@
  * 
  */
 
-let fs = require("fs");
-let { render } = require("mustache");
+const fs = require("fs").promises;
+const { render } = require("mustache");
 const axios = require("axios");
 
 // Recursively loop through each object to ensure a defined 'children' property (even if empty)
@@ -28,11 +28,41 @@ const ensureChildrenProperty = (arr) => {
     return arr;
 }
 
-axios.get('https://kg.diffbot.com/kg/ontology')
-.then((response) => {
-    
-    // Template Model for Industry Categories
-    var industries = response['data']['taxonomies']['IndustryCategory']['categories'];
+// // Read the file
+// fs.readFile("ontology.tmp.json", 'utf8', (err, data) => {
+//     if (err) {
+//         console.error('Error reading the file:', err);
+//         return;
+//     }
+
+//     try {
+//         // Parse the JSON content
+//         const jsonData = JSON.parse(data);
+//         console.log('JSON Data:', jsonData);
+//     } catch (err) {
+//         console.error('Error parsing JSON:', err);
+//     }
+// });
+
+
+// axios.get('https://kg.diffbot.com/kg/ontology')
+// .then((response) => {
+//     // generateIndustries(response['data'])
+// })
+// .then(());
+
+const run = async () => {
+    // const response = await axios.get('https://kg.diffbot.com/kg/ontology')
+    // const result = await fs.writeFile('ontology.json', JSON.stringify(response['data']))
+    console.log("Reading saved ontology file...")
+    const ontology = await fs.readFile('ontology.tmp.json', 'utf8')
+    const jsonData = JSON.parse(ontology);
+    generateIndustries(jsonData)
+}
+
+const generateIndustries = async (ont) => {
+// Template Model for Industry Categories
+    var industries = ont['taxonomies']['OrganizationCategory']['categories'];
     industries = ensureChildrenProperty(industries);
     // -- Convert to Array for mustache template iteration
     let industriesArray = [];
@@ -41,7 +71,7 @@ axios.get('https://kg.diffbot.com/kg/ontology')
     }
 
     // Template Model for Employment Categories
-    var employmentCategories = response['data']['taxonomies']['EmploymentCategory']['categories'];
+    var employmentCategories = ont['taxonomies']['EmploymentCategory']['categories'];
     employmentCategories = ensureChildrenProperty(employmentCategories);
     // -- Convert to Arrays for mustache template iteration
     let employmentCategoriesByType = {};
@@ -52,26 +82,63 @@ axios.get('https://kg.diffbot.com/kg/ontology')
         employmentCategoriesByType[employmentCategories[category]["info"]["facet"]].push(employmentCategories[category]);
     }
 
+    // Template Model for Article Categories
+    var articleCategories = ont['taxonomies']['ArticleCategory']['categories'];
+    articleCategories = ensureChildrenProperty(articleCategories);
+    // -- Convert to Array for mustache template iteration
+    let articleCategoriesArray = [];
+    for (let industry in articleCategories) {
+        articleCategoriesArray.push(articleCategories[industry]);
+    }
+
+    // Template Model for Technology Categories
+    var technologyCategories = ont['taxonomies']['TechnologyCategory']['categories'];
+    technologyCategories = ensureChildrenProperty(technologyCategories);
+    // -- Convert to Array for mustache template iteration
+    let technologyCategoriesArray = [];
+    for (let cat in technologyCategories) {
+        technologyCategoriesArray.push(technologyCategories[cat]);
+    }
+
     var templateModel = {
         industries: industriesArray,
-        employmentCategories: employmentCategoriesByType
+        employmentCategories: employmentCategoriesByType,
+        articleCategories: articleCategoriesArray,
+        technologyCategories: technologyCategoriesArray
     };
 
 
     // Get Industries Template
-    let industriesTemplate = fs.readFileSync("./static/md/kg-industries.md").toString();
+    let industriesTemplate = await fs.readFile("./static/md/kg-industries.md", 'utf-8')
 
     // Render Industries Template
     let industriesOutput = render(industriesTemplate, templateModel);
-    console.log(`Rendered Industry Reference! Writing Markdown...`);
-    fs.writeFileSync(`../docs/kg-industry-list.md`, industriesOutput);
+    console.log(`Rendered Industry Reference! Generating Markdown.../docs/kg-industry-list.md`);
+    await fs.writeFile(`../docs/kg-industry-list.md`, industriesOutput);
 
     // Get Employment Categories Template
-    let employmentCategoriesTemplate = fs.readFileSync("./static/md/kg-employment-categories.md").toString();
+    let employmentCategoriesTemplate = await fs.readFile("./static/md/kg-employment-categories.md", 'utf-8')
 
     // Render Employment Categories Template
     let employmentCategoriesOutput = render(employmentCategoriesTemplate, templateModel);
-    console.log(`Rendered Employment Categories Reference! Writing Markdown...`);
-    fs.writeFileSync(`../docs/kg-employment-categories-list.md`, employmentCategoriesOutput);
+    console.log(`Rendered Employment Categories Reference! Generating Markdown.../docs/kg-employment-categories-list.md`);
+    await fs.writeFile(`../docs/kg-employment-categories-list.md`, employmentCategoriesOutput);
+
+    // Get Article Categories Template
+    let articleCategoriesTemplate = await fs.readFile("./static/md/kg-article-categories.md", 'utf-8')
+
+    // Render Article Categories Template
+    let articleCategoriesOutput = render(articleCategoriesTemplate, templateModel);
+    console.log(`Rendered Article Category Reference! Generating Markdown.../docs/kg-article-categories-list.md`);
+    await fs.writeFile(`../docs/kg-article-categories-list.md`, articleCategoriesOutput);
+
+    // Get Techbology Categories Template
+    let technologyCategoriesTemplate = await fs.readFile("./static/md/kg-technology-categories.md", 'utf-8')
+
+    // Render Technology Categories Template
+    let technologyCategoriesOutput = render(technologyCategoriesTemplate, templateModel);
+    console.log(`Rendered Technology Category Reference! Generating Markdown.../docs/kg-technology-categories-list.md`);
+    await fs.writeFile(`../docs/kg-technology-categories-list.md`, technologyCategoriesOutput);
+}
 
-});
\ No newline at end of file
+run()
\ No newline at end of file
diff --git a/website/generateOntology.js b/website/generateOntology.js
index 027ad94f..572b0886 100644
--- a/website/generateOntology.js
+++ b/website/generateOntology.js
@@ -17,8 +17,8 @@ let fs = require("fs");
 let { render } = require("mustache");
 const axios = require("axios");
 
-// Delete this
-const DIFFBOTTOKEN = ""
+let args = process.argv.slice(2);
+const DIFFBOTTOKEN = args[0] ? args[0] : "";
 
 // Template helpers
 const templateHelpers = {
@@ -31,95 +31,140 @@ const templateHelpers = {
 
 // Supported entity types and props
 var entityTypes = {
-    DiffbotEntity: { 
-        title: "All",
-        id: "kg-ont-diffbotentity",
-        description: "All Knowledge Graph entities will include the fields below, which are often generalized, linking, or metadata attributes common to all records. \n\nSee the left navigation panel for fields and attributes for specific entities,",
-        helpers: templateHelpers
-    },
-    Article: { 
-        title: "Article",
-        id: "kg-ont-article",
-        description: "The article entity type encompasses news, blog posts, and article content known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
-        helpers: templateHelpers,
-        exampleRecord: 'type:Article title:"The web as a database: The biggest knowledge graph ever"'
-    },
-    Organization: { 
-        title: "Organization",
-        id: "kg-ont-organization",
-        description: "The organization entity type encompasses corporations, local businesses, non-profits, and other organizations known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
-        helpers: templateHelpers,
-        exampleRecord: 'type:Organization name:"IBM"'
-    },
-    Person: { 
-        title: "Person",
-        id: "kg-ont-person",
-        description: "The person entity type encompasses all people known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
-        helpers: templateHelpers,
-        exampleRecord: 'type:Person name:"Tom Wheeler" revSortBy:importance'
-    },
-    Place: { 
-        title: "Place",
-        id: "kg-ont-place",
-        description: "The place entity type encompasses cities, landmarks, countries, administrative areas, and other locations known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
-        helpers: templateHelpers,
-        exampleRecord: 'type:Place revSortBy:importance'
-    },
-    CreativeWork: { 
-        title: "CreativeWork",
-        id: "kg-ont-creativework",
-        description: "The Creative Work entity type encompasses movies, tv shows, musicals, scripts, and other creative works known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
-        helpers: templateHelpers,
-        exampleRecord: 'type:CreativeWork name:"American Masters" revSortBy:importance'
-    },
-    Product: { 
-        title: "Product",
-        id: "kg-ont-product",
-        description: "The product entity type encompasses products found throughout the web known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
-        helpers: templateHelpers,
-        exampleRecord: 'type:Product name:"Gold Down Alternative Sleeping Pillows"'
-    },
-    Image: { 
-        title: "Image",
-        id: "kg-ont-image",
-        description: "The Image entity type encompasses images found throughout the web and known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
-        helpers: templateHelpers,
-        exampleRecord: 'type:Image title:"a visualization of the knowledge graph"'
-    },
-    Video: { 
-        title: "Video",
-        id: "kg-ont-video",
-        description: "The Video entity type encompasses videos found throughout the web and known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
-        helpers: templateHelpers,
-        exampleRecord: 'type:Video title:"Deconstructing Data Complexity and the Case for AI-Driven Smart Data Discovery"'
-    },
-    Event: { 
-        title: "Event",
-        id: "kg-ont-event",
-        description: "The Event entity type encompasses webinars, meet ups, conferences, and other events known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
-        helpers: templateHelpers,
-        exampleRecord: 'type:Event name:"Talent Connect"'
-    },
-    Discussion: { 
-        title: "Discussion",
-        id: "kg-ont-discussion",
-        description: "The Discussion entity type encompasses forum and other similar discussions found throughout the web and known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
-        helpers: templateHelpers
-    },
-    AdministrativeArea: { 
-        title: "AdministrativeArea",
-        id: "kg-ont-administrativearea",
-        description: "The Administrative Area entity type encompasses all cities, regions, counties, sub-regions, provinces, and countries known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
-        helpers: templateHelpers,
-        exampleRecord: 'type:AdministrativeArea name:"California"'
-    },
-    // ROLE ONTOLOGY IS MISSING
-    // Role: { 
-    //     title: "Role",
-    //     id: "kg-ont-role",
-    //     description: "The Role entity type encompasses all roles known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
-    //     helpers: templateHelpers
-    // },
+  DiffbotEntity: {
+    title: "All",
+    id: "kg-ont-diffbotentity",
+    description:
+      "All Knowledge Graph entities will include the fields below, which are often generalized, linking, or metadata attributes common to all records. \n\nSee the left navigation panel for fields and attributes of specific entities.",
+    helpers: templateHelpers,
+  },
+  Article: {
+    title: "Article",
+    id: "kg-ont-article",
+    description:
+      "The article entity type encompasses news, blog posts, and article content known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
+    helpers: templateHelpers,
+    exampleRecord:
+      'type:Article title:"The web as a database: The biggest knowledge graph ever"',
+  },
+  Organization: {
+    title: "Organization",
+    id: "kg-ont-organization",
+    description:
+      "The organization entity type encompasses corporations, local businesses, non-profits, and other organizations known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
+    helpers: templateHelpers,
+    exampleRecord: 'type:Organization name:"IBM"',
+  },
+  Person: {
+    title: "Person",
+    id: "kg-ont-person",
+    description:
+      "The person entity type encompasses all people known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
+    helpers: templateHelpers,
+    exampleRecord: 'type:Person name:"Tom Wheeler" revSortBy:importance',
+  },
+  Place: {
+    title: "Place",
+    id: "kg-ont-place",
+    description:
+      "The place entity type encompasses cities, landmarks, countries, administrative areas, and other locations known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
+    helpers: templateHelpers,
+    exampleRecord: "type:Place revSortBy:importance",
+  },
+  CreativeWork: {
+    title: "CreativeWork",
+    id: "kg-ont-creativework",
+    description:
+      "The Creative Work entity type encompasses movies, tv shows, musicals, scripts, and other creative works known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
+    helpers: templateHelpers,
+    exampleRecord:
+      'type:CreativeWork name:"American Masters" revSortBy:importance',
+  },
+  Product: {
+    title: "Product",
+    id: "kg-ont-product",
+    description:
+      "The product entity type encompasses retail products found throughout the web known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
+    helpers: templateHelpers,
+    exampleRecord: 'type:Product site:"newegg.com"',
+  },
+  Image: {
+    title: "Image",
+    id: "kg-ont-image",
+    description:
+      "The Image entity type encompasses images found throughout the web and known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
+    helpers: templateHelpers,
+    exampleRecord: 'type:Image title:"Mike Tung"',
+  },
+  Video: {
+    title: "Video",
+    id: "kg-ont-video",
+    description:
+      "The Video entity type encompasses videos found throughout the web and known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
+    helpers: templateHelpers,
+    exampleRecord: 'type:Video title:"Diffbot"',
+  },
+  Event: {
+    title: "Event",
+    id: "kg-ont-event",
+    description:
+      "The Event entity type encompasses webinars, meet ups, conferences, and other events known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
+    helpers: templateHelpers,
+    exampleRecord: 'type:Event name:"Talent Connect"',
+  },
+  Discussion: {
+    title: "Discussion",
+    id: "kg-ont-discussion",
+    description:
+      "The Discussion entity type encompasses forum and other similar discussions found throughout the web and known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
+    helpers: templateHelpers,
+  },
+  JobPost: {
+    title: "JobPost",
+    id: "kg-ont-JobPost",
+    description:
+      "The Job Post entity type encompasses all job postings found throughout the web and known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
+    helpers: templateHelpers,
+    exampleRecord: 'type:JobPost employer.name:"Diffbot"',
+  },
+  Research: {
+    title: "Research",
+    id: "kg-ont-research",
+    description:
+      "The Research entity type includes public access research papers and journal articles found throughout the web and known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
+    helpers: templateHelpers,
+    exampleRecord: 'type:Research title:"KnowledgeNet"',
+  },
+  LegalEntity: {
+    title: "LegalEntity",
+    id: "kg-ont-legalentity",
+    description:
+      "The LegalEntity entity type includes companies and organizations with legal status and identifiers.",
+    helpers: templateHelpers,
+    exampleRecord: 'type:LegalEntity name:"GENERAL MOTORS"',
+  },
+  // CURRENTLY BREAKS EXAMPLRECORD GENERATION
+  // faqs: {
+  //     title: "FAQ",
+  //     id: "kg-ont-faq",
+  //     description: "The FAQ entity type is a specialized type of List of Frequently Asked Questions found in various public websites.",
+  //     helpers: templateHelpers,
+  //     exampleRecord: 'type:FAQ faqs.q:"Zika"'
+  // }
+  // AdministrativeArea: {
+  //     title: "AdministrativeArea",
+  //     id: "kg-ont-administrativearea",
+  //     description: "A sub-type of [Place](doc:place), the Administrative Area entity type encompasses all cities, regions, counties, sub-regions, provinces, and countries known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
+  //     helpers: templateHelpers,
+  //     exampleRecord: 'type:AdministrativeArea name:"California"'
+  // },
+  // ROLE ONTOLOGY IS MISSING
+  // Role: {
+  //     title: "Role",
+  //     id: "kg-ont-role",
+  //     description: "The Role entity type encompasses all roles known to the Knowledge Graph. \n\nNote that fields are not guaranteed to exist in every entity record.",
+  //     helpers: templateHelpers
+  // },
 };
 
 // Translates technical content type definitions to layman descriptions & examples
@@ -133,11 +178,6 @@ const typeS = {
 
 const buildFieldExample = (fieldName, fieldEntity, ontDocs, exampleRecord) => {
 
-    // console.log("Field Name: ", fieldName);
-    // console.log(fieldEntity);
-    // console.log(ontDocs);
-    // console.log("Example Record: ", exampleRecord);
-
     // Truncate example records
     if (exampleRecord && exampleRecord[fieldName]) {
         exampleRecord[fieldName] = Array.isArray(exampleRecord[fieldName]) ? exampleRecord[fieldName].slice(0, 3) : exampleRecord[fieldName];
@@ -184,6 +224,9 @@ const buildFieldExample = (fieldName, fieldEntity, ontDocs, exampleRecord) => {
                 compositeSubFieldNames.forEach(subFieldName => {
                     if (fieldEntity["fields"][fieldName]["isList"] === true) {
                         example[0][subFieldName] = buildFieldExample(subFieldName, compositeField, ontDocs, exampleRecord && exampleRecord[fieldName] ? exampleRecord[fieldName] : false);
+                        if (subFieldName === "investors") {
+                            console.log(example[0][subFieldName])
+                        }
                     }
                     else {
                         example[subFieldName] = buildFieldExample(subFieldName, compositeField, ontDocs, exampleRecord && exampleRecord[fieldName] ? exampleRecord[fieldName] : false);
@@ -192,7 +235,7 @@ const buildFieldExample = (fieldName, fieldEntity, ontDocs, exampleRecord) => {
             }
         }
         else {
-            console.error(`WARNING: The definition for composite field ${fieldEntity["fields"][fieldName]["type"]} does not exist in the ontology`)
+            console.warn(`WARNING: The definition for composite field ${fieldEntity["fields"][fieldName]["type"]} does not exist in the ontology`)
         }
     }
     // Linked Entity Type
@@ -251,9 +294,21 @@ const getExamples = (entityTypes) => {
     for (entityIndex in entities) {
         let entityTemplate = entityTypes[entities[entityIndex]];
         if (entityTemplate['exampleRecord']) {
-            promises.push(axios.get(`https://kg.diffbot.com/kg/dql_endpoint?type=query&token=${DIFFBOTTOKEN}&size=1&query=${encodeURIComponent(entityTemplate['exampleRecord'])}`).then((response) => {
+            promises.push(axios.get(`https://kg.diffbot.com/kg/v3/dql?type=query&token=${DIFFBOTTOKEN}&size=1&query=${encodeURIComponent(entityTemplate['exampleRecord'])}`).then((response) => {
                 let example = {}
-                example[entityTemplate.title] = response.data.data[0];
+                try {
+                    if (response.data.hits > 0) {
+                        example[entityTemplate.title] = response.data.data[0]['entity']        
+                    }
+                    else {
+                        console.log(`No example record found for ${entityTemplate['title']}. (${entityTemplate['exampleRecord']})`)    
+                    }
+                }
+                catch (error) {
+                    console.log(error)
+                    console.log(response)
+                }
+                
                 return example;
             }));
         }
@@ -266,7 +321,16 @@ getExamples(entityTypes)
 .then((examples) => {
     for (exampleIndex in examples) {
         let entityType = Object.keys(examples[exampleIndex])[0];
-        entityTypes[entityType]['exampleRecord'] = examples[exampleIndex][entityType];
+        try {
+            if (entityType !== null || entityType !== undefined) {
+                entityTypes[entityType]['exampleRecord'] = examples[exampleIndex][entityType]
+            }
+        }
+        catch (e) {
+            console.log(examples[exampleIndex])
+            console.log(e)
+        }
+
     }
 
     return axios.get('https://kg.diffbot.com/kg/ontology')
@@ -286,7 +350,7 @@ getExamples(entityTypes)
 
         // Render Template
         let output = render(template, entityModel);
-        console.log(`Rendered ${entityModel.title} Ontology! Writing Markdown...`);
+        console.log(`Rendered ${entityModel.title} Ontology! Generating Markdown... /docs/${entityModel.id}.md`);
         fs.writeFileSync(`../docs/${entityModel.id}.md`, output);
 
     }
diff --git a/website/ontology.json b/website/ontology.json
new file mode 100644
index 00000000..cf9f5fe7
--- /dev/null
+++ b/website/ontology.json
@@ -0,0 +1 @@
+{"metadata":{"kg-version":"369","binary-version":"0.9.178","generated":"1716500121"},"types":{"AdministrativeArea":{"name":"AdministrativeArea","typeHierarchy":["Place","DiffbotEntity"],"fields":{"geonameId":{"name":"geonameId","description":"","isFact":true,"isEnum":false,"isList":false,"isPrimitive":true,"type":"Integer","isDeprecated":false,"isComposite":false,"isEntity":false,"documented":true,"tracksFirstSeen":false}},"documented":true},"Album":{"name":"Album","typeHierarchy":["CreativeWork","Work","DiffbotEntity"],"fields":{"languages":{"name":"languages","description":"This is the language in which the work is originally created.","isFact":true,"isEnum":false,"isList":true,"isPrimitive":true,"type":"String","isDeprecated":false,"isComposite":false,"isEntity":false,"documented":true,"tracksFirstSeen":false},"trackPosition":{"name":"trackPosition","description":"","isFact":true,"isEnum":false,"isList":false,"isPrimitive":true,"type":"Integer","isDeprecated":false,"isComposite":false,"isEntity":false,"documented":true,"tracksFirstSeen":false},"artistCredit":{"name":"artistCredit","description":"Artist Credit String","isFact":true,"isEnum":false,"isList":false,"isPrimitive":true,"type":"String","isDeprecated":false,"isComposite":false,"isEntity":false,"documented":true,"tracksFirstSeen":false},"creditedArtists":{"name":"creditedArtists","description":"List of credited artists","isFact":true,"isEnum":false,"isList":true,"isPrimitive":false,"type":"LinkedEntity","leType":["Person","Organization"],"isDeprecated":false,"isComposite":true,"isEntity":false,"documented":true,"tracksFirstSeen":false},"numTracks":{"name":"numTracks","description":"","isFact":true,"isEnum":false,"isList":false,"isPrimitive":true,"type":"Integer","isDeprecated":false,"isComposite":false,"isEntity":false,"documented":true,"tracksFirstSeen":false}},"documented":true},"Article":{"name":"Article","typeHierarchy":["GlobalIndexDiffbotEntity"],"fields":{"date":{"name":"date","description":"","isFact":false,"isEnum":false,"isList":false,"isPrimitive":false,"type":"DDateTime","isDeprecated":false,"isComposite":true,"isEntity":false,"documented":true,"tracksFirstSeen":false},"sentiment":{"name":"sentiment","description":"Sentiment of the article. 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Reality","info":{"iabv2Id":"639"}}]},{"name":"Television","info":{"iabv2Id":"640"}},{"name":"Travel","info":{"iabv2Id":"653"},"children":[{"name":"Travel Locations","info":{"iabv2Id":"655"},"children":[{"name":"Africa Travel","info":{"iabv2Id":"656"}},{"name":"Asia Travel","info":{"iabv2Id":"657"}},{"name":"Australia and Oceania Travel","info":{"iabv2Id":"658"}},{"name":"Europe Travel","info":{"iabv2Id":"659"}},{"name":"North America Travel","info":{"iabv2Id":"660"}},{"name":"Polar Travel","info":{"iabv2Id":"661"}},{"name":"South America Travel","info":{"iabv2Id":"662"}}]},{"name":"Travel Preparation and Advice","info":{"iabv2Id":"663"}},{"name":"Travel Type","info":{"iabv2Id":"664"},"children":[{"name":"Adventure Travel","info":{"iabv2Id":"665"}},{"name":"Air Travel","info":{"iabv2Id":"672"}},{"name":"Beach Travel","info":{"iabv2Id":"673"}},{"name":"Budget Travel","info":{"iabv2Id":"675"}},{"name":"Business Travel","info":{"iabv2Id":"676"}},{"name":"Camping","info":{"iabv2Id":"677"}},{"name":"Cruises","info":{"iabv2Id":"678"}},{"name":"Day Trips","info":{"iabv2Id":"679"}},{"name":"Family Travel","info":{"iabv2Id":"666"}},{"name":"Honeymoons and Getaways","info":{"iabv2Id":"667"}},{"name":"Hotels and Motels","info":{"iabv2Id":"668"}},{"name":"Rail Travel","info":{"iabv2Id":"669"}},{"name":"Road Trips","info":{"iabv2Id":"670"}},{"name":"Spas","info":{"iabv2Id":"671"}}]}]},{"name":"Video Gaming","info":{"iabv2Id":"680"},"children":[{"name":"Console Games","info":{"iabv2Id":"681"}},{"name":"Mobile Games","info":{"iabv2Id":"683"}},{"name":"PC Games","info":{"iabv2Id":"684"}},{"name":"eSports","info":{"iabv2Id":"682"}}]}]}},"dev-notes":"The ontology has these top-level elements:\n1. `metadata`: General metadata about the ontology. See [Metadata](#Metadata) section.\n2. `types`: Entity type definitions. See [Types](#Types) section.\n3. `composites`: Non-primitive type definitions referenced by entity fields. See [Composites](#Composites) section.\n4. `enums`: Enumerations referenced by entity fields. See [Enums](#Enums) section.\n5. `taxonomies`: Taxonomies referenced by entity fields. See [Taxonomies](#Taxonomies) section.\n6. `dev-notes`: These notes (don't we all loooove self-references)\n\n# Metadata\nMetadata has the following general structure:\n```\n\"metadata\": {\n   \"kg-version\": \"175\",\n   \"binary-version\": \"0.3.15\",\n   \"generated\": \"1613687623\"\n}\n```\n1. `kg-version`: Version of the KG for which this ontology was generated\n2. `binary-version`: Internal developer metadata\n3. `generated`: Unix timestamp when this metadata was generated\n\n# Types\nType definitions have the following general structure:\n```\n\"Person\": {\n   \"name\": \"Person\",\n   \"typeHierarchy\": [\n      \"DiffbotEntity\"\n   ],\n   \"taxonomy\": null,\n   \"fields\": {\n      \"twitterUri\": {\n         \"name\": \"twitterUri\",\n         \"description\": \"Link to the Twitter profile of the Person entity\",\n         \"isFact\": true,\n         \"isEnum\": false,\n         \"isList\": false,\n         \"isPrimitive\": false,\n         \"type\": \"DiffbotUrl\",\n         \"isDeprecated\": false\n      },\n      ...\n   }\n}\n```\n1. `name`: Name of the entity\n2. `typeHierarchy`: Type hierarchy of the entity. `DiffbotEntity` is the root type. An entity inherits all fields from its hierarchy. The `typeHierarchy` is ordered from closest to farthest ancestor. Example:\n```\n   \"LocalBusiness\": {\n      \"typeHierarchy\": [\n         \"Organization\",\n         \"DiffbotEntity\"\n      ],\n```\n3. `taxonomy`: Refers to a taxonomy for this entity, if one exists. See [Taxonomies](#Taxonomies) section. \n4. `fields`: Entity fields. See [Fields section](#Fields).\n\n### Fields\nEntity fields have the following general structure:\n```\n   \"categories\":{\n      \"name\":\"categories\",\n      \"description\":\"Industry categories\",\n      \"isFact\":true,\n      \"isEnum\":false,\n      \"isList\":true,\n      \"isPrimitive\":false,\n      \"type\":\"LinkedEntity\",\n      \"leType\":[\n         \"IndustryCategory\"\n      ],\n      \"isDeprecated\":false\n   }\n```\n1. `name`: Name of the field\n2. `description`: Description of the field\n3. `isFact`: A value of `true` indicates that this field is a Fact field. Fact fields contain provenance and confidence information, aside from the value of the fact. See [Facts](#Facts) section for structure of fact.\n4. `isEnum`: A value of `true` indicates that this field is an enumeration. Enumeration values are listed in the `enum` section of the ontology. See section on [Enums](#Enums) .\n5. `isList`: A value of `true` indicates that this field is an array field and can hold multiple values.\n6. `isPrimitive`: A value of `true` indicates that this field is a primitive. See sections on [Primitives](#Primitives)  and [Composites](#Composites) for more information on field datatypes.\n7. `type`: Type of the field. Fields can be [Primitives](#Primitives), [Composites](#Composites), [Enums](#Enums) or one of the [Entity Types](#Types).\n8. `leType`: Indicates that this fields refers to a LinkedEntity and lists the Entity Types that this LinkedEntity can refer to. See section on [LinkedEntity](#LinkedEntity) for details.\n9. `isDeprecated`: Indicates if the field is deprecated and may not be supported in the future.\n\n### Facts\nFact fields contain provenance and confidence information, aside from the value of the fact. Fact fields have the following general structure:\n```\n\"twitterUri\": {\n   \"explicitOrigin\": [\n      \"angel.co/diffbot\",\n      \"crunchbase.com/organization/diffbot\",\n      \"wikidata.org/entity/Q17052069\"\n   ],\n   \"confidence\": \"0.60\",\n   \"value\": \"twitter.com/diffbot\"\n}\n```\n### Primitives\nThe following primitives types are supported:\n- `Integer`: Integer types such as `byte`, `short`, `int`, `long`\n- `Float`: Decimal types such as `float`, `double`\n- `Boolean`: Boolean type\n- `String`: String type\n- `URL`: This is a special type of String which represents a URL\n\n### LinkedEntity\nLinkedEntity fields refer to other other Entity Types. For example, a `Organization.founders` is a LinkedEntity that refers to `Person` type.\n\nLinkedEntities have the `type` fields declared as `LinkedEntity` and the possible Entity Types are listed in the `leType` element.\n```\n   \"type\": \"LinkedEntity\",\n   \"leType\": [ \"Person\" ],\n```\n\n# Composites\nComposites are complex datatypes. They have the following general structure:\n```\n   \"Contact\":{\n      \"name\":\"Contact\",\n      \"fields\":{\n         \"contactString\":{\n            \"name\":\"contactString\",\n            \"description\":\"A field such as email address etc.\",\n            \"isFact\":false,\n            \"isEnum\":false,\n            \"isList\":false,\n            \"isPrimitive\":true,\n            \"type\":\"String\",\n            \"isDeprecated\":false\n         },\n         ...\n      }\n   }\n```\n1. `name`: Name of the Composite\n2. `description`: Description of the Composite\n3. `fields`: Composite fields. They have the same structure as an Entity field. See [Fields section](#Fields).\n \n# Enums\nEnums have the following general structure:\n```\n   \"EyeColor\":{\n      \"name\":\"EyeColor\",\n      \"values\":[\n         \"Black\",\n         \"Brown\",\n         \"Blue\",\n         ...\n      ]\n   }\n```\n1. `name`: Name of the Enum\n2. `description`: Description of the Enum\n3. `values`: Possible values of the composite\n\n# Taxonomies\nIf an Entity Type has an associated taxonomy, it'll be mentioned in the `taxonomy` field of the Type definition. The taxonomy definition itself is under the top-level `taxonomies` element.\n\n```\n   \"IndustryCategory\":{\n      \"name\":\"IndustryCategory\",\n      \"taxonomy\": \"IndustryCategory\",\n      \"typeHierarchy\":[\n         \"Intangible\",\n         \"DiffbotEntity\"\n      ]\n   }\n```\n\nTaxonomies have the following general structure:\n```\n[\n   {\n      \"name\":\"Food And Drink Companies\",\n      \"diffbotId\": \"EXXXXXXXXXXX\",\n      \"info\": {\n         \"naicsMapping\":\"311000\"\n      }\n      \"children\":[\n         {\n            \"name\": \"Animal Food Manufacturers\",\n            \"info\": {\n               \"naicsMapping\":\"311000\"\n            }\n            \"children\":[\n                ...\n            ]\n         }\n      ]\n   },\n   ...\n]\n```\n1. `name`: Name of the category\n2. `diffbotId`: DiffbotId of the category, if an entity exists in Diffbot KG corresponding to the category\n3. `info`: Information specific to the taxonomy. The structure of this element is not formally defined and can change depending on the specific taxonomy.\n4. `children`: Child categories. Children have the same JSON structure as the parent and taxonomies can be arbitrarily deeply nested. "}
\ No newline at end of file
diff --git a/website/ontology.tmp.json b/website/ontology.tmp.json
new file mode 100644
index 00000000..5596a70e
--- /dev/null
+++ b/website/ontology.tmp.json
@@ -0,0 +1 @@
+{"types":{"AdministrativeArea":{"name":"AdministrativeArea","typeHierarchy":["Place","DiffbotEntity"],"fields":{"geonameId":{"name":"geonameId","description":"","isFact":true,"isEnum":false,"isList":false,"isPrimitive":true,"type":"Integer","isDeprecated":false,"isComposite":false,"isEntity":false,"documented":true,"tracksFirstSeen":false}},"documented":true},"Album":{"name":"Album","typeHierarchy":["CreativeWork","Work","DiffbotEntity"],"fields":{"languages":{"name":"languages","description":"This is the language in which the work is originally created.","isFact":true,"isEnum":false,"isList":true,"isPrimitive":true,"type":"String","isDeprecated":false,"isComposite":false,"isEntity":false,"documented":true,"tracksFirstSeen":false},"trackPosition":{"name":"trackPosition","description":"","isFact":true,"isEnum":false,"isList":false,"isPrimitive":true,"type":"Integer","isDeprecated":false,"isComposite":false,"isEntity":false,"documented":true,"tracksFirstSeen":false},"artistCredit":{"name":"artistCredit","description":"Artist Credit String","isFact":true,"isEnum":false,"isList":false,"isPrimitive":true,"type":"String","isDeprecated":false,"isComposite":false,"isEntity":false,"documented":true,"tracksFirstSeen":false},"creditedArtists":{"name":"creditedArtists","description":"List of credited artists","isFact":true,"isEnum":false,"isList":true,"isPrimitive":false,"type":"LinkedEntity","leType":["Person","Organization"],"isDeprecated":false,"isComposite":true,"isEntity":false,"documented":true,"tracksFirstSeen":false},"numTracks":{"name":"numTracks","description":"","isFact":true,"isEnum":false,"isList":false,"isPrimitive":true,"type":"Integer","isDeprecated":false,"isComposite":false,"isEntity":false,"documented":true,"tracksFirstSeen":false}},"documented":true},"Article":{"name":"Article","typeHierarchy":["GlobalIndexDiffbotEntity"],"fields":{"date":{"name":"date","description":"","isFact":false,"isEnum":false,"isList":false,"isPrimitive":false,"type":"DDateTime","isDeprecated":false,"isComposite":true,"isEntity":false,"documented":true,"tracksFirstSeen":false},"sentiment":{"name":"sentiment","description":"Sentiment of the article. 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Companies","info":{"naicsMapping":"483212","sicMapping":"4489"}},{"name":"Public Transport Operators","info":{"naicsMapping":"485110","sicMapping":"4729"}},{"name":"Railway Companies","info":{"naicsMapping":"482110","sicMapping":"4000"}},{"name":"Ridesharing And Taxi Companies","info":{"naicsMapping":"485310","sicMapping":"4121"}},{"name":"Vehicle Rental Companies","info":{"naicsMapping":"532111","sicMapping":"7514"}}]},{"name":"Utility Companies","info":{"naicsMapping":"221000","sicMapping":"4900"},"children":[{"name":"Electricity Distribution Companies","info":{"naicsMapping":"221122","sicMapping":"4911"}},{"name":"Gas Distribution Companies","info":{"naicsMapping":"221210","sicMapping":"4924"}},{"name":"Heat Distribution Companies","info":{"naicsMapping":"221330","sicMapping":"4961"}},{"name":"Waste And Recycling Companies","info":{"naicsMapping":"562000","sicMapping":"4953"},"children":[{"name":"Recycling Companies","info":{"naicsMapping":"562920","sicMapping":"4953"}}]},{"name":"Water Distribution Companies","info":{"naicsMapping":"221310","sicMapping":"4941"}}]}]}},"dev-notes":"The ontology has these top-level elements:\n1. `metadata`: General metadata about the ontology. See [Metadata](#Metadata) section.\n2. `types`: Entity type definitions. See [Types](#Types) section.\n3. `composites`: Non-primitive type definitions referenced by entity fields. See [Composites](#Composites) section.\n4. `enums`: Enumerations referenced by entity fields. See [Enums](#Enums) section.\n5. `taxonomies`: Taxonomies referenced by entity fields. See [Taxonomies](#Taxonomies) section.\n6. `dev-notes`: These notes (don't we all loooove self-references)\n\n# Metadata\nMetadata has the following general structure:\n```\n\"metadata\": {\n   \"kg-version\": \"175\",\n   \"binary-version\": \"0.3.15\",\n   \"generated\": \"1613687623\"\n}\n```\n1. `kg-version`: Version of the KG for which this ontology was generated\n2. `binary-version`: Internal developer metadata\n3. `generated`: Unix timestamp when this metadata was generated\n\n# Types\nType definitions have the following general structure:\n```\n\"Person\": {\n   \"name\": \"Person\",\n   \"typeHierarchy\": [\n      \"DiffbotEntity\"\n   ],\n   \"taxonomy\": null,\n   \"fields\": {\n      \"twitterUri\": {\n         \"name\": \"twitterUri\",\n         \"description\": \"Link to the Twitter profile of the Person entity\",\n         \"isFact\": true,\n         \"isEnum\": false,\n         \"isList\": false,\n         \"isPrimitive\": false,\n         \"type\": \"DiffbotUrl\",\n         \"isDeprecated\": false\n      },\n      ...\n   }\n}\n```\n1. `name`: Name of the entity\n2. `typeHierarchy`: Type hierarchy of the entity. `DiffbotEntity` is the root type. An entity inherits all fields from its hierarchy. The `typeHierarchy` is ordered from closest to farthest ancestor. Example:\n```\n   \"LocalBusiness\": {\n      \"typeHierarchy\": [\n         \"Organization\",\n         \"DiffbotEntity\"\n      ],\n```\n3. `taxonomy`: Refers to a taxonomy for this entity, if one exists. See [Taxonomies](#Taxonomies) section. \n4. `fields`: Entity fields. See [Fields section](#Fields).\n\n### Fields\nEntity fields have the following general structure:\n```\n   \"categories\":{\n      \"name\":\"categories\",\n      \"description\":\"Industry categories\",\n      \"isFact\":true,\n      \"isEnum\":false,\n      \"isList\":true,\n      \"isPrimitive\":false,\n      \"type\":\"LinkedEntity\",\n      \"leType\":[\n         \"IndustryCategory\"\n      ],\n      \"isDeprecated\":false\n   }\n```\n1. `name`: Name of the field\n2. `description`: Description of the field\n3. `isFact`: A value of `true` indicates that this field is a Fact field. Fact fields contain provenance and confidence information, aside from the value of the fact. See [Facts](#Facts) section for structure of fact.\n4. `isEnum`: A value of `true` indicates that this field is an enumeration. Enumeration values are listed in the `enum` section of the ontology. See section on [Enums](#Enums) .\n5. `isList`: A value of `true` indicates that this field is an array field and can hold multiple values.\n6. `isPrimitive`: A value of `true` indicates that this field is a primitive. See sections on [Primitives](#Primitives)  and [Composites](#Composites) for more information on field datatypes.\n7. `type`: Type of the field. Fields can be [Primitives](#Primitives), [Composites](#Composites), [Enums](#Enums) or one of the [Entity Types](#Types).\n8. `leType`: Indicates that this fields refers to a LinkedEntity and lists the Entity Types that this LinkedEntity can refer to. See section on [LinkedEntity](#LinkedEntity) for details.\n9. `isDeprecated`: Indicates if the field is deprecated and may not be supported in the future.\n\n### Facts\nFact fields contain provenance and confidence information, aside from the value of the fact. Fact fields have the following general structure:\n```\n\"twitterUri\": {\n   \"explicitOrigin\": [\n      \"angel.co/diffbot\",\n      \"crunchbase.com/organization/diffbot\",\n      \"wikidata.org/entity/Q17052069\"\n   ],\n   \"confidence\": \"0.60\",\n   \"value\": \"twitter.com/diffbot\"\n}\n```\n### Primitives\nThe following primitives types are supported:\n- `Integer`: Integer types such as `byte`, `short`, `int`, `long`\n- `Float`: Decimal types such as `float`, `double`\n- `Boolean`: Boolean type\n- `String`: String type\n- `URL`: This is a special type of String which represents a URL\n\n### LinkedEntity\nLinkedEntity fields refer to other other Entity Types. For example, a `Organization.founders` is a LinkedEntity that refers to `Person` type.\n\nLinkedEntities have the `type` fields declared as `LinkedEntity` and the possible Entity Types are listed in the `leType` element.\n```\n   \"type\": \"LinkedEntity\",\n   \"leType\": [ \"Person\" ],\n```\n\n# Composites\nComposites are complex datatypes. They have the following general structure:\n```\n   \"Contact\":{\n      \"name\":\"Contact\",\n      \"fields\":{\n         \"contactString\":{\n            \"name\":\"contactString\",\n            \"description\":\"A field such as email address etc.\",\n            \"isFact\":false,\n            \"isEnum\":false,\n            \"isList\":false,\n            \"isPrimitive\":true,\n            \"type\":\"String\",\n            \"isDeprecated\":false\n         },\n         ...\n      }\n   }\n```\n1. `name`: Name of the Composite\n2. `description`: Description of the Composite\n3. `fields`: Composite fields. They have the same structure as an Entity field. See [Fields section](#Fields).\n \n# Enums\nEnums have the following general structure:\n```\n   \"EyeColor\":{\n      \"name\":\"EyeColor\",\n      \"values\":[\n         \"Black\",\n         \"Brown\",\n         \"Blue\",\n         ...\n      ]\n   }\n```\n1. `name`: Name of the Enum\n2. `description`: Description of the Enum\n3. `values`: Possible values of the composite\n\n# Taxonomies\nIf an Entity Type has an associated taxonomy, it'll be mentioned in the `taxonomy` field of the Type definition. The taxonomy definition itself is under the top-level `taxonomies` element.\n\n```\n   \"IndustryCategory\":{\n      \"name\":\"IndustryCategory\",\n      \"taxonomy\": \"IndustryCategory\",\n      \"typeHierarchy\":[\n         \"Intangible\",\n         \"DiffbotEntity\"\n      ]\n   }\n```\n\nTaxonomies have the following general structure:\n```\n[\n   {\n      \"name\":\"Food And Drink Companies\",\n      \"diffbotId\": \"EXXXXXXXXXXX\",\n      \"info\": {\n         \"naicsMapping\":\"311000\"\n      }\n      \"children\":[\n         {\n            \"name\": \"Animal Food Manufacturers\",\n            \"info\": {\n               \"naicsMapping\":\"311000\"\n            }\n            \"children\":[\n                ...\n            ]\n         }\n      ]\n   },\n   ...\n]\n```\n1. `name`: Name of the category\n2. `diffbotId`: DiffbotId of the category, if an entity exists in Diffbot KG corresponding to the category\n3. `info`: Information specific to the taxonomy. The structure of this element is not formally defined and can change depending on the specific taxonomy.\n4. `children`: Child categories. Children have the same JSON structure as the parent and taxonomies can be arbitrarily deeply nested. "}
\ No newline at end of file
diff --git a/website/pages/en/index.js b/website/pages/en/index.js
index bc680aa6..947dfdda 100644
--- a/website/pages/en/index.js
+++ b/website/pages/en/index.js
@@ -23,11 +23,7 @@ class HomeSplash extends React.Component {
 
     const SplashContainer = props => (
       <div className="homeContainer">
-        <div class="fixedHeaderContainer" style={{backgroundColor: '#fa383e'}}>
-          <div class="headerWrapper wrapper"><header style={{textAlign: 'center', display: 'block', paddingTop: '5px'}}><a style={{display: 'block'}} target="_blank" href="https://docs.diffbot.com/docs/en/explain-letsencrypt-certificate-expiration">SSL Error? Read here for why and how to solve it!</a></header>
-          </div>
-        </div>
-        <div className="homeSplashFade" style={{paddingTop:"40px"}}>
+        <div className="homeSplashFade">
           <div className="wrapper homeWrapper">{props.children}</div>
         </div>
       </div>
diff --git a/website/pages/kgapi.html b/website/pages/kgapi.html
index 77d9c598..d82d43c4 100644
--- a/website/pages/kgapi.html
+++ b/website/pages/kgapi.html
@@ -41,7 +41,7 @@ <h2 class="headerTitleWithLogo">Docs Suite</h2></a><div class="navigationWrapper
                 <li class=""><a href="/docs/en/error-intro" target="_self">Debugging</a></li>
                   </ul></nav></div></header></div></div>
     <main role="main">
-      <redoc spec-url='https://kg.diffbot.com/kg/openapi.json'></redoc>
+      <redoc spec-url='https://kg.diffbot.com/kg/dql/openapi.json'></redoc>
       <script src="https://cdn.jsdelivr.net/npm/redoc@next/bundles/redoc.standalone.js"> </script>
     </main>
   
@@ -68,4 +68,5 @@ <h2 class="headerTitleWithLogo">Docs Suite</h2></a><div class="navigationWrapper
   });
 </script>
 
-</body></html>
\ No newline at end of file
+</body></html>
+
diff --git a/website/sidebars.json b/website/sidebars.json
index e1479950..4060d994 100644
--- a/website/sidebars.json
+++ b/website/sidebars.json
@@ -150,6 +150,25 @@
         "ids": ["api-event"]
       }
     ]
+  },
+   "list-api": {
+    "List API": [
+      {
+        "type": "subcategory",
+        "label": "Intro",
+        "ids": ["api-intro-list"]
+      },
+      {
+        "type": "subcategory",
+        "label": "Basics",
+        "ids": ["api-basics-list"]
+      },
+      {
+        "type": "subcategory",
+        "label": "API",
+        "ids": ["api-list"]
+      }
+    ]
   },
   "custom-api": {
     "Custom API": [
@@ -279,7 +298,7 @@
       {
         "type": "subcategory",
         "label": "Tools and Usage",
-        "ids": ["kg-accessing", "kg-clients", "dql-excel", "dql-endpoints", "kg-filtering"]
+        "ids": ["kg-accessing", "kg-clients", "dql-excel","kg-enhance-quickstart", "dql-endpoints", "kg-filtering"]
       },
       {
         "type": "subcategory",
@@ -309,7 +328,8 @@
     ],
     "References": [
       "kg-industry-list",
-      "kg-employment-categories-list"
+      "kg-employment-categories-list",
+      "kg-article-categories-list"
     ]
   },
   "nl": {
diff --git a/website/static/img/enhance-get-started/enhance-four.PNG b/website/static/img/enhance-get-started/enhance-four.PNG
new file mode 100644
index 00000000..7c7325e8
Binary files /dev/null and b/website/static/img/enhance-get-started/enhance-four.PNG differ
diff --git a/website/static/img/enhance-get-started/enhance-one.PNG b/website/static/img/enhance-get-started/enhance-one.PNG
new file mode 100644
index 00000000..84c7c685
Binary files /dev/null and b/website/static/img/enhance-get-started/enhance-one.PNG differ
diff --git a/website/static/img/enhance-get-started/enhance-three.PNG b/website/static/img/enhance-get-started/enhance-three.PNG
new file mode 100644
index 00000000..16bc54e0
Binary files /dev/null and b/website/static/img/enhance-get-started/enhance-three.PNG differ
diff --git a/website/static/img/enhance-get-started/enhance-two.PNG b/website/static/img/enhance-get-started/enhance-two.PNG
new file mode 100644
index 00000000..2f7136d0
Binary files /dev/null and b/website/static/img/enhance-get-started/enhance-two.PNG differ
diff --git a/website/static/img/enhance-get-started/g-sheets-function.gif b/website/static/img/enhance-get-started/g-sheets-function.gif
new file mode 100644
index 00000000..50380d29
Binary files /dev/null and b/website/static/img/enhance-get-started/g-sheets-function.gif differ
diff --git a/website/static/img/enhance-get-started/install-g-sheets.gif b/website/static/img/enhance-get-started/install-g-sheets.gif
new file mode 100644
index 00000000..4481efeb
Binary files /dev/null and b/website/static/img/enhance-get-started/install-g-sheets.gif differ
diff --git a/website/static/js/app.js b/website/static/js/app.js
index 32d4f3a0..09ff9744 100644
--- a/website/static/js/app.js
+++ b/website/static/js/app.js
@@ -4,6 +4,15 @@ function resizeIframe(obj) {
   obj.style.height =
     obj.contentWindow.document.documentElement.scrollHeight + "px";
 }
+//Add google analytics
+
+  window.dataLayer = window.dataLayer || [];
+  function gtag(){dataLayer.push(arguments);}
+  gtag('js', new Date());
+
+  gtag('config', 'UA-74291704-1');
+
+
 
 (function (funcName, baseObj) {
   // The public function name defaults to window.docReady
@@ -97,6 +106,7 @@ docReady(function () {
   let dd1html =
     '<a href="/docs/en/kg-index" class="dropbtn">Knowledge Graph</a><div class="dropdown-content">';
   dd1html += '<a href="/kgapi">KG API Reference</a>';
+  dd1html += '<a href="/docs/en/dql-quickstart">KG Getting Started</a>';
   dd1html += '<a href="/enhance">Enhance API Reference</a>';
   dd1html += '<a href="/docs/en/kg-ont-diffbotentity">Ontology</a>';
   dd1html += '<a href="/docs/en/kg-industry-list">Industry Hierarchy</a>';
@@ -112,10 +122,11 @@ docReady(function () {
   dd2html += '<a href="/docs/en/api-intro-product">Product API</a>';
   dd2html += '<a href="/docs/en/api-intro-article">Article API</a>';
   dd2html += '<a href="/docs/en/api-intro-analyze">Analyze API</a>';
-  dd2html += '<a href="/docs/en/api-event">Event API</a>';
+  dd2html += '<a href="/docs/en/api-intro-event">Event API</a>';
   dd2html += '<a href="/docs/en/api-intro-image">Image API</a>';
   dd2html += '<a href="/docs/en/api-intro-video">Video API</a>';
   dd2html += '<a href="/docs/en/api-intro-discussion">Discussion API</a>';
+  dd2html += '<a href="/docs/en/api-intro-list">List API</a>';
   dd2html += '<a href="/docs/en/api-intro-custom">Custom API</a>';
   dd2html += '<a href="/docs/en/api-intro-account">Account API</a>';
   dd2html += "</div>";
@@ -191,18 +202,9 @@ docReady(function () {
     }
   }
 
-  // Add fathom analytics
-  let script = document.createElement("script");
-  script.setAttribute("src", "https://cdn.usefathom.com/3.js");
-  script.setAttribute("site", "OGXCNLPJ");
-  document.querySelector("body").appendChild(script);
-
-  // Add Plausible
-  let plausible = document.createElement("script");
-  plausible.setAttribute("src", "https://stats.diffbot.com/js/index.js");
-  plausible.setAttribute("data-domain", "docs.diffbot.com");
-  plausible.setAttribute("async", "async");
-  plausible.setAttribute("defer", "defer");
-  document.querySelector("head").appendChild(plausible);
+  //google analytics external script
+  let google_analytics = document.createElement("script");
+  google_analytics.setAttribute("src","https://www.googletagmanager.com/gtag/js?id=UA-74291704-1")
+  document.querySelector("body").appendChild(google_analytics);
 
 });
diff --git a/website/static/md/entity-ontology.md b/website/static/md/entity-ontology.md
index 709d9b7a..faa2ad25 100644
--- a/website/static/md/entity-ontology.md
+++ b/website/static/md/entity-ontology.md
@@ -1,11 +1,18 @@
 ---
+warning: DO NOT EDIT THIS DOC DIRECTLY (SEE ORIGIN)
+origin: https://kg.diffbot.com/kg/ontology
 id: {{ id }}
 title: {{ title }}
+generatedBy: generateOntology.js
 ---
 
 {{ description }}
 
->New to the Diffbot Knowledge Graph? [Start here](dql-quickstart).
+For convenience, a complete ontology source in JSON format is also [available here](https://kg.diffbot.com/kg/ontology).
+
+> 🙋 
+> 
+> New to the Diffbot Knowledge Graph? [Start here](doc:getting-started-with-diffbot-knowledge-graph).
 
 ## {{ title }} Fields
 {{ #fields }}
diff --git a/website/static/md/kg-article-categories.md b/website/static/md/kg-article-categories.md
new file mode 100644
index 00000000..03f77ae3
--- /dev/null
+++ b/website/static/md/kg-article-categories.md
@@ -0,0 +1,45 @@
+---
+id: kg-article-categories-list
+title: Article Categories
+onPageNav: false
+---
+
+**BETA** — Article categories provide structured context to the topic discussed in a particular piece of text. Unlike [tags](kg-ont-article#tags), categories describe the text as a whole and tend to be more abstract. 
+
+> As of Nov 17, 2021, article categories is in beta and is only supported through [Article Extract](api-intro-article). Ontology and access may be subject to change at any time.
+
+Here's a sample request to extract categories alongside your article extraction —
+
+
+```python
+https://api.diffbot.com/v3/article?token=TOKEN&url=https://blog.diffbot.com/a-less-biased-way-to-discern-media-bias-using-knowledge-graph-enhanced-ai/&naturalLanguage=categories
+```
+
+The category list below outlines all possible categories that may be returned by Diffbot Extract.
+
+| Primary Category    | Secondary Category | Tertiary Category                   |  Quaternary Category |
+| ------------------- | ------------------ | ----------------------------------- | ---- |
+{{ #articleCategories }}
+|  {{ name }}         |                   |   |  |
+{{ #children }}
+|          |  {{ name }}                 |  |  |
+{{ #children }}
+|          |                  | {{ name }}  |  |
+{{ #children }}
+|          |                  |   | {{ name }} |
+{{ /children }}
+{{ /children }}
+{{ /children }}
+{{ /articleCategories }}
+
+
+<style>
+/* Hides the Right-Hand Secondary Nav for a Full Width Industry Table */
+.onPageNav {
+    display: none;
+}
+/* Hides the Unnecessary Prev/Next Buttons for this Reference Doc */
+.docs-prevnext {
+    display: none;
+}
+</style>
\ No newline at end of file
diff --git a/website/static/md/kg-employment-categories.md b/website/static/md/kg-employment-categories.md
index 2fdf803e..9401fc98 100644
--- a/website/static/md/kg-employment-categories.md
+++ b/website/static/md/kg-employment-categories.md
@@ -2,6 +2,7 @@
 id: kg-employment-categories-list
 title: Employment Categories
 onPageNav: false
+generatedBy: generateIndustries.js
 ---
 
 Employment categories (see [employments ontology reference](kg-ont-person#employments)) are canonicalized Domains, Seniority, and/or Roles inferred from a given person's employment title and description. Employment categories are only applicable for the [Person data type](kg-ont-person).
@@ -28,6 +29,18 @@ An employment category reflecting various career types (e.g. *Human Resources*,
 | ------------------- | ------------------ | ----------------------------------- | ---- | --- | -- |
 {{ #employmentCategories.Domain }}
 | {{ info.facet }}          |  {{ name }}         |                   |   |  |  |
+{{ #children }}
+|                     |          |  {{ name }}                 |  |  |  |
+{{ #children }}
+|                     |          |                  | {{ name }}  |  |  |
+{{ #children }}
+|                     |          |                  |   | {{ name }} |  |
+{{ #children }}
+|                     |          |                  |   |  | {{ name }} |
+{{ /children }}
+{{ /children }}
+{{ /children }}
+{{ /children }}
 {{ /employmentCategories.Domain }}
 
 ## By Role
diff --git a/website/static/md/kg-industries.md b/website/static/md/kg-industries.md
index 3d5126ea..10fcc944 100644
--- a/website/static/md/kg-industries.md
+++ b/website/static/md/kg-industries.md
@@ -1,36 +1,41 @@
 ---
 id: kg-industry-list
-title: Organization Industries
+title: Organization Categories
 onPageNav: false
+generatedBy: generateIndustries.js
 ---
 
-This reference is helpful for narrowing down queries for organizations on the [Diffbot Knowledge Graph](dql-quickstart) by [industry](kg-ont-organization#industries). Diffbot Knowledge Graph Search supports querying by industry names or NAICS codes. Feel free to use either.
+> 📘 Looking for Industries?
+> 
+> This reference now contains the new taxonomy for industries v2, keyed as `categories`, and which contains over 250% more categories than the [previous industries taxonomy](<>) .
+> 
+> Legacy organization industries will be deprecated **Friday, August 30, 2024**.
+> 
+> Please see the [migration guide](<>)  for a complete overview of the changes.
+
+This reference is helpful for narrowing down queries for organizations on the [Diffbot Knowledge Graph](dql-quickstart) by [industry category](ont-organization#categories). Diffbot Knowledge Graph Search supports querying by category names, NAICS, or SIC codes. Feel free to use any of them.
 
 An example [DQL](dql-index) query using an industry on this list might look like this —
 
 ```
-type:Organization industry:"Medical Associations"
+type:Organization categories:"Software Companies"
 ```
 
-| Primary Industry    | Secondary Industry | Tertiary Industry | NAICS                   |
-| ------------------- | ------------------ | ----------------- | ----------------------- |
-{{ #industries }}
-| {{ name }}          |                    |                   | {{ info.naicsMapping }} |
-{{ #children }}
-|                     | {{ name }}         |                   | {{ info.naicsMapping }} |
-{{ #children }}
-|                     |                    | {{ name }}        | {{ info.naicsMapping }} |
+
+| L1 Category    | L2 Category | L3 Category | L4 Category | L5 Category | NAICS                   | SIC                   |
+| ------------------- | ------------------ | ----------------- | ----------------- | ----------------- | ----------------------- | --------------------- |
+{{ #industries }}                                                                                                    
+| {{ name }}          |                    |                   |                   |                   | {{ info.naicsMapping }} | {{ info.sicMapping }} |
+{{ #children }}                                                                                                      
+|                     | {{ name }}         |                   |                   |                   | {{ info.naicsMapping }} | {{ info.sicMapping }} |
+{{ #children }}                                                                                                      
+|                     |                    | {{ name }}        |                   |                   | {{ info.naicsMapping }} | {{ info.sicMapping }} |
+{{ #children }}                                                                                                      
+|                     |                    |                   | {{ name }}        |                   | {{ info.naicsMapping }} | {{ info.sicMapping }} |
+{{ #children }}                                                                                                      
+|                     |                    |                   |                   | {{ name }}        | {{ info.naicsMapping }} | {{ info.sicMapping }} |
+{{ /children }}
+{{ /children }}
 {{ /children }}
 {{ /children }}
 {{ /industries }}
-
-<style>
-/* Hides the Right-Hand Secondary Nav for a Full Width Industry Table */
-.onPageNav {
-    display: none;
-}
-/* Hides the Unnecessary Prev/Next Buttons for this Reference Doc */
-.docs-prevnext {
-    display: none;
-}
-</style>
\ No newline at end of file
diff --git a/website/static/md/kg-technology-categories.md b/website/static/md/kg-technology-categories.md
new file mode 100644
index 00000000..9fe6fe60
--- /dev/null
+++ b/website/static/md/kg-technology-categories.md
@@ -0,0 +1,44 @@
+---
+id: kg-technology-categories-list
+title: Technology Categories
+onPageNav: false
+---
+
+The list below outlines all possible categories that may be returned within the `technographics` attribute in Organization entity types. A list of all categories may also be accessed as their own entity type (`type:TechnologyCategory`) or found in the `technologyCategories` attribute in its parent `type:Technology`. See the DQL examples below for more color.
+
+```python
+# To find organizations that use "Assisted Living Software"
+type:Organization technographics.categories:"Assisted Living Software"
+```
+
+```python
+# To find all technologies associated with the technology category "Real Estate Agency Software"
+type:Technology technologyCategories:"Real Estate Agency Software"
+```
+
+| Primary Category    | Secondary Category | Tertiary Category                   |  Quaternary Category |
+| ------------------- | ------------------ | ----------------------------------- | ---- |
+{{ #technologyCategories }}
+|  {{ name }}         |                   |   |  |
+{{ #children }}
+|          |  {{ name }}                 |  |  |
+{{ #children }}
+|          |                  | {{ name }}  |  |
+{{ #children }}
+|          |                  |   | {{ name }} |
+{{ /children }}
+{{ /children }}
+{{ /children }}
+{{ /technologyCategories }}
+
+
+<style>
+/* Hides the Right-Hand Secondary Nav for a Full Width Industry Table */
+.onPageNav {
+    display: none;
+}
+/* Hides the Unnecessary Prev/Next Buttons for this Reference Doc */
+.docs-prevnext {
+    display: none;
+}
+</style>
\ No newline at end of file