This is the code of the paper Modeling Document Causal Structure with A Hypergraph for Event Causality Identification.

A Neural Causal Hypergraph Model (NCHM) to encode both document causal structureand pairwise event semantics for the ECI task.

Illustration of our NCHM framework.

• python==3.7.13
• transformers==4.15.0
• matplotlib==3.5.3
• numpy==1.21.5
• scikit-learn==1.0.2
• scipy==1.7.3
• torch==1.11.0
• torch_scatter==2.0.9
• torch_geometric==2.1.0.post1
• tqdm==4.64.1

All training commands are listed in parameter.py. For example, you can run the following commands to train NCHM on the EventStoryLine v0.9 datasets.

# the EventStoryLine v0.9
python train.py --fold 1
python train.py --fold 2
python train.py --fold 3
python train.py --fold 4
python train.py --fold 5

We refer to the code of Hyper-Conv. Thanks for their contributions.