SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference

@article{Zellers2018SWAGAL,
  title={SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference},
  author={Rowan Zellers and Yonatan Bisk and Roy Schwartz and Yejin Choi},
  journal={ArXiv},
  year={2018},
  volume={abs/1808.05326}
}

• Rowan Zellers, Yonatan Bisk, +1 author Yejin Choi
• Published in EMNLP 2018
• DOI:10.18653/v1/d18-1009

Given a partial description like "she opened the hood of the car," humans can reason about the situation and anticipate what might come next ("then, she examined the engine"). In this paper, we introduce the task of grounded commonsense inference, unifying natural language inference and commonsense reasoning. We present SWAG, a new dataset with 113k multiple choice questions about a rich spectrum of grounded situations. To address the recurring challenges of the annotation artifacts and human… CONTINUE READING

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