Repository for paper "SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference"
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README.md

swagaf

SWAG dataset. More info is at rowanzellers.com/swag.

Setting up your environment

To create an environment you will need to intall Python 3.1, PyTorch 3.1, and AllenNLP. These requirements are listed in requirements.txt.

You will also need to set PYTHONPATH to the swagaf directory. You can do this by running the following command from the swagaf folder.

export PYTHONPATH=$(pwd)

Alternatively, you can build and run the included Dockerfile to create an environment.

docker build -t swagaf .
docker run -it swagaf

Common use cases

There is additional documentation in the subfolders.

  • data/ contains the SWAG dataset.
  • swag_baslines/ contains baseline implementations and instructions for how to run them.

Most people will not need to look at create_swag or raw_data but it's there if you need it!

Citing

@inproceedings{zellers2018swagaf,
    title={SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference},
    author={Zellers, Rowan and Bisk, Yonatan and Schwartz, Roy and Choi, Yejin},
    booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
    year={2018}
}