# INCANT ## Raw Data Raw data used to generate INCANT networks is scraped from GDELT using `Final_Datasets/data_pull.py`. The output for each domain is stored in `Final_Datasets/[domain name].csv`. ​ ## Network Generation INCANT networks are generated from raw data using `process.py`. The output networks are stored in `Final_Datasets/[domain name]_network.csv`. These csv files contain columns for source and target nodes, as well as additional metadata. ​ Helper functions for the QA task and coreference resolution used in network generation are found under the `QA` and `COREF` directories respectively. Template questions for QA are found in `template.py`. ​ # TAMPA ## Networks ​ Input networks to TAMPA generated by INCANT are found in the `input/` directory. The contents of this directory consist of the 6 domains analyzed in the paper. The outputs of message passing on these INCANT networks are found in the `output/` directory. This directory contains outputs of message passing on both the INCANT and PERM networks. ​ ## Message Passing and Clustering Functions to perform message passing on the INCANT networks are found in `msg_passing.py`. Examples of using these can be found in `run.py`. Functions to perform clustering on node embeddings can be found in `parse_data.py`. Helpful functions for visualizing results can be found in `display.py`. Examples of using these can be found in `msg_passing.ipynb`. ​ ## Baselines Functions for both baseline models are found in `baselines.py`.