README.md

metadata

annotations_creators:
  - expert-generated
language_creators:
  - expert-generated
language:
  - en
license:
  - cc-by-4.0
multilinguality:
  - monolingual
size_categories:
  - n<1K
source_datasets:
  - original
task_categories:
  - multiple-choice
task_ids:
  - multiple-choice-coreference-resolution
paperswithcode_id: wsc
pretty_name: Winograd Schema Challenge
dataset_info:
  - config_name: wsc285
    features:
      - name: text
        dtype: string
      - name: pronoun
        dtype: string
      - name: pronoun_loc
        dtype: int32
      - name: quote
        dtype: string
      - name: quote_loc
        dtype: int32
      - name: options
        sequence: string
      - name: label
        dtype:
          class_label:
            names:
              '0': '0'
              '1': '1'
      - name: source
        dtype: string
    splits:
      - name: test
        num_bytes: 52281
        num_examples: 285
    download_size: 113235
    dataset_size: 52281
  - config_name: wsc273
    features:
      - name: text
        dtype: string
      - name: pronoun
        dtype: string
      - name: pronoun_loc
        dtype: int32
      - name: quote
        dtype: string
      - name: quote_loc
        dtype: int32
      - name: options
        sequence: string
      - name: label
        dtype:
          class_label:
            names:
              '0': '0'
              '1': '1'
      - name: source
        dtype: string
    splits:
      - name: test
        num_bytes: 49674
        num_examples: 273
    download_size: 113235
    dataset_size: 49674

The original Winograd Schema Challenge (WSC) as hosted by Ernest Davis

Dataset Description

• Homepage: https://cs.nyu.edu/faculty/davise/papers/WinogradSchemas/WS.html
• Paper: https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.729.9814&rep=rep1&type=pdf

Dataset Summary

A Winograd schema is a pair of sentences that differ in only one or two words and that contain an ambiguity that is resolved in opposite ways in the two sentences and requires the use of world knowledge and reasoning for its resolution. The schema takes its name from a well-known example by Terry Winograd:

The city councilmen refused the demonstrators a permit because they [feared/advocated] violence.

If the word is "feared", then "they" presumably refers to the city council; if it is "advocated" then "they" presumably refers to the demonstrators.

Dataset Structure

Data Instances

Each instance contains a text passage with a designated pronoun and two possible answers indicating which entity in the passage the pronoun represents. An example instance looks like the following:

{
  'label': 0,
  'options': ['The city councilmen', 'The demonstrators'],
  'pronoun': 'they',
  'pronoun_loc': 63,
  'quote': 'they feared violence',
  'quote_loc': 63,
  'source': '(Winograd 1972)',
  'text': 'The city councilmen refused the demonstrators a permit because they feared violence.'
}

Data Fields

• text (str): The text sequence
• options (list[str]): The two entity options that the pronoun may be referring to
• label (int): The index of the correct option in the options field
• pronoun (str): The pronoun in the sequence to be resolved
• pronoun_loc (int): The starting position of the pronoun in the sequence
• quote (str): The substr with the key action or context surrounding the pronoun
• quote_loc (int): The starting position of the quote in the sequence
• source (str): A description of the source who contributed the example

Licensing Information

This work is licensed under a Creative Commons Attribution 4.0 International License.

Citation Information

The Winograd Schema Challenge including many of the examples here was proposed by Levesque et al 2012:

@inproceedings{levesque2012winograd,
  title={The winograd schema challenge},
  author={Levesque, Hector and Davis, Ernest and Morgenstern, Leora},
  booktitle={Thirteenth International Conference on the Principles of Knowledge Representation and Reasoning},
  year={2012},
  organization={Citeseer}
}

Contributions

Thanks to @joeddav for adding this dataset.