self-supervised-rule-learning

A neuro-symbolic approach to self-learn rules that serve as interpretable knowledge to perform relation linking in knowledge base question answering systems.

Cluttr Experiments

1. Download clutrr dataset.
2. Pre-process the data using python clutrr/preprocess_data.py --input_data_path <clutrr data path> --output_data_path <pre-processed data path>.
3. Perform rule learning and generate test results by invoking python clutrr/self_learn_rules.py --train_data_json_path <train json file path> --test_data_json_path <test json file path>.