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Event Causality Identification via Structure optimization and Reinforcement Learning

GenSORL

Requirements

The dependency packages can be installed with the command:

pip install -r requirements.txt

Datasets

  1. Download the dataset (It is recommended to skip this step and proceed directly to Step[2] and Step[3])
    EventStoryLine
    Causal-TimeBank

  2. Download the data utilized by the authors of the paper

    All data, Please contact with writer;

  1. Extract and overwrite
    Step[1] - Extract the folder and copy the dataset to the datasets folder.
    Step[2] - Extract the folder to the project directory, overwriting the existing datasets folder.

Usage

  1. Prepare data
    Extract data from the ESL dataset: In the preprocessor.py file located at .\datasets\preprocessor.py, set dataset = 'ESL'.(Default)
    Extract data from the Causal-TB dataset: In the preprocessor.py file located at .\datasets\preprocessor.py, set dataset = 'Causal-TB'.
    and run:
python datasets/preprocessor/preprocessor.py
  1. Train model:
sh ESL_bash.sh

or Select training dataset: In the datasets.py file located at .\data_modules\datasets.py, change "ESL" to "Causal-TB" in line 143.

sh CausalTB_bash.sh

Acknowledgement

Part of our code is borrowed from code, many thanks.

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