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WinoGrande

Paper

Title: WinoGrande: An Adversarial Winograd Schema Challenge at Scale

Abstract: https://arxiv.org/abs/1907.10641

WinoGrande is a collection of 44k problems, inspired by Winograd Schema Challenge (Levesque, Davis, and Morgenstern 2011), but adjusted to improve the scale and robustness against the dataset-specific bias. Formulated as a fill-in-a-blank task with binary options, the goal is to choose the right option for a given sentence which requires commonsense reasoning.

NOTE: This evaluation of Winogrande uses partial evaluation as described by Trinh & Le in Simple Method for Commonsense Reasoning (2018). See: https://arxiv.org/abs/1806.02847

Homepage: https://leaderboard.allenai.org/winogrande/submissions/public

Citation

@article{sakaguchi2019winogrande,
    title={WinoGrande: An Adversarial Winograd Schema Challenge at Scale},
    author={Sakaguchi, Keisuke and Bras, Ronan Le and Bhagavatula, Chandra and Choi, Yejin},
    journal={arXiv preprint arXiv:1907.10641},
    year={2019}
}

Groups and Tasks

Groups

  • Not part of a group yet.

Tasks

  • winogrande

Checklist

For adding novel benchmarks/datasets to the library:

  • Is the task an existing benchmark in the literature?
    • Have you referenced the original paper that introduced the task?
    • If yes, does the original paper provide a reference implementation? If so, have you checked against the reference implementation and documented how to run such a test?

If other tasks on this dataset are already supported:

  • Is the "Main" variant of this task clearly denoted?
  • Have you provided a short sentence in a README on what each new variant adds / evaluates?
  • Have you noted which, if any, published evaluation setups are matched by this variant?