ARM

This repository provides the code for ARM (Attention Retrieval Model), a novel self-attention framework for flexible entity relation extraction from biological literature.

Authors and Contributors: Prashant Srivastava, Saptarshi Bej, Kristian Schultz, Kristina Yordanova, Olaf Wolkenhauer

Steps

1. Create a new folder in root dir named 'Data'.

2. Download Datasets for AIR, TRRUST, GAD, ChemProt, BioGRID, and Elangovan et al. and save them in /Data.

3. Register at Entrez Programming Utilities (E-utilities) and obtain Email and api-key.

4. Create a file named 'config.py' containing entrez email and api-key as:
   

entrez_api_key = 'Your-Entrez-email'
entrez_email = 'Your-Entrez-apikey'

4. Navigate to /Preprocessing dir and run the jupyter-notebooks for all datasets.
   Running all the notebooks in this directory with produce entity normalized datasets that are required in next step.
5. Run Typed Interactions.ipynb for typed relations Case Study.
6. Run Untyped Interactions.ipynb for untyped relations Case Study.