GitHub

Put EventStoryLine, CausalTM, EventCausalityData, SemEval, and FrameNet datasets in the current directory.
Run read_document.py to build all intra-sentence examples for EventStoryLine.
Run preprecess_*.py to generate BERT-based examples for difference datasets and settings.
Run train_mix.py to train the model, with different settings.

Name		Name	Last commit message	Last commit date
Latest commit History 5 Commits
README.md		README.md
baseline_OP.py		baseline_OP.py
baseline_PPMI1.py		baseline_PPMI1.py
baseline_PPMI_CONTAINS.py		baseline_PPMI_CONTAINS.py
concept_net_util.py		concept_net_util.py
coref_evaluation.py		coref_evaluation.py
create_gold_document.py		create_gold_document.py
dataset.py		dataset.py
eval_script.py		eval_script.py
generate_training_data.py		generate_training_data.py
mlp1.py		mlp1.py
model.py		model.py
preprocess.py		preprocess.py
preprocess_bert.py		preprocess_bert.py
preprocess_causaltb.py		preprocess_causaltb.py
preprocess_conceptnet.py		preprocess_conceptnet.py
preprocess_eventcausalitydata.py		preprocess_eventcausalitydata.py
preprocess_framenet.py		preprocess_framenet.py
preprocess_semeval.py		preprocess_semeval.py
read_document.py		read_document.py
semeval_dataset.py		semeval_dataset.py
semeval_model.py		semeval_model.py
semeval_train_mix.py		semeval_train_mix.py
train_mix.py		train_mix.py
util.py		util.py
util_causaltb.py		util_causaltb.py
util_eventcausalitydata.py		util_eventcausalitydata.py
util_framenet.py		util_framenet.py
util_semeval.py		util_semeval.py

Provide feedback