Specifind is a Python toolkit built to automatically extract species occurrence information from unstructured ecological literature. It identifies scientific species names, geographic entities, and the relations connecting them—unlocking occurrence data hidden in text.

The toolkit integrates OCR, layout analysis, Named Entity Recognition, Coreference Resolution, and Relation Extraction into a unified and traceable pipeline. It is powered by a newly developed, expertly annotated dataset of 1,000+ ecological abstracts spanning biogeography, botany, entomology, mycology, and zoology.

• 📄 Science-OCR for domain-optimized OCR of scientific papers
• 🔍 NER for scientific species names & geographic entities
• 🌍 Relation Extraction connecting species to locations
• 🧠 FastCOREF for high-performance coreference resolution
• 🧩 Built on spaCy for extensibility, speed, and NLP interoperability
• 🧱 Full pipeline for text & PDF extraction
• 🧭 Traceability that links extractions back to the original text

pip install specifind

from specifind import Specifind

s = Specifind()

s.analyze("Upupa epops is an exotic bird. It is widely extended over Spain.")

# or

s.analyze_file("path/to/file.pdf")

# Output:
# {
#     "species": [
#         "Upupa epops"
#     ],
#     "geography": [
#         "Spain"
#     ],
#     "occurrences": {
#         "Upupa epops": [
#             "Spain"
#         ]
#     },
#     "evidence": {
#         "Upupa epops": {
#             "Spain": [
#                 "It is widely extended over Spain."
#             ]
#         }
#     }
# }

python3.11 -m venv venv
source venv/bin/activate

Install Specifind

pip install --upgrade pip
pip install specifind

Open R, load the reticulate library and configure the virtual environment.

# Load reticulate package
library(reticulate)
use_virtualenv("venv", required = TRUE)

Import Specifind and run the analysis.

# Import the Specifind class
Specifind <- import("specifind")$Specifind

# Create an instance
s <- Specifind(use_gpu=TRUE)

# Option A: Run the analysis on a text string
text <- "Upupa epops is an exotic bird. It is widely extended over Spain."
result <- s$analyze(text, coref = TRUE, return_doc = FALSE)

# Option B: Run analysis on a PDF file
result <- s$analyze_file("path/to/document.pdf", coref = TRUE, dpi = 96L)

Initializes the OCR engine.

Process and extract information from a PDF file.

Parameters

Returns

• Dictionary including parsed entities, relations and evidences.
• (optional) internal doc object (if return_doc=True)

Process and extract information directly from raw text.

Parameters

Returns

• Dictionary including parsed entities, relations and evidences.
• (optional) internal doc object

Species & Locations

Occurrences

Contributions, issue reports, and feature suggestions are welcome. Feel free to open a Pull Request or discussion.

Specifind is licensed under AGPL-3.0. See LICENSE for details.

If you use Specifind in your research, please cite our pre-print:

Tomas, G. D., Josep, F. A., Anna, D., María, B., Alejandro, R., Noemi, C., & Tommaso, C. (2025). Specifind: A Natural Language Processing Tool for Automating Species Occurrence (Re-) Discovery from Scientific Literature. bioRxiv, 2025-12.

@article{specifind2025,
  title   = {Specifind: A Natural Language Processing Tool for Automating Species Occurrence (Re-)Discovery from Scientific Literature},
  author  = {Golomb Durán Tomás, Díaz Anna, Barroso María, Far Antoni Josep, Roldán Alejandro, Cancellario Tommaso},
  year    = {2025},
  journal = {BioRxiv},
  url     = {https://doi.org/10.64898/2025.12.24.696373}
}