README.md

metadata

annotations_creators:
  - expert-generated
language:
  - en
language_creators:
  - expert-generated
license:
  - cc-by-4.0
multilinguality:
  - monolingual
pretty_name: Modified Winograd Schema Challenge (MWSC)
size_categories:
  - n<1K
source_datasets:
  - extended|winograd_wsc
task_categories:
  - multiple-choice
task_ids:
  - multiple-choice-coreference-resolution
paperswithcode_id: null
dataset_info:
  features:
    - name: sentence
      dtype: string
    - name: question
      dtype: string
    - name: options
      sequence: string
    - name: answer
      dtype: string
  splits:
    - name: train
      num_bytes: 11022
      num_examples: 80
    - name: test
      num_bytes: 15220
      num_examples: 100
    - name: validation
      num_bytes: 13109
      num_examples: 82
  download_size: 19197
  dataset_size: 39351

Dataset Card for The modified Winograd Schema Challenge (MWSC)

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: http://decanlp.com
• Repository: https://github.com/salesforce/decaNLP
• Paper: The Natural Language Decathlon: Multitask Learning as Question Answering
• Point of Contact: Bryan McCann, Nitish Shirish Keskar
• Size of downloaded dataset files: 19.20 kB
• Size of the generated dataset: 39.35 kB
• Total amount of disk used: 58.55 kB

Dataset Summary

Examples taken from the Winograd Schema Challenge modified to ensure that answers are a single word from the context. This Modified Winograd Schema Challenge (MWSC) ensures that scores are neither inflated nor deflated by oddities in phrasing.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

• Size of downloaded dataset files: 0.02 MB
• Size of the generated dataset: 0.04 MB
• Total amount of disk used: 0.06 MB

An example looks as follows:

{
    "sentence": "The city councilmen refused the demonstrators a permit because they feared violence.",
    "question": "Who feared violence?",
    "options": [ "councilmen", "demonstrators" ],
    "answer": "councilmen"
}

Data Fields

The data fields are the same among all splits.

default

• sentence: a string feature.
• question: a string feature.
• options: a list of string features.
• answer: a string feature.

Data Splits

name	train	validation	test
default	80	82	100

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

More Information Needed

Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

Our code for running decaNLP has been open sourced under BSD-3-Clause.

We chose to restrict decaNLP to datasets that were free and publicly accessible for research, but you should check their individual terms if you deviate from this use case.

From the Winograd Schema Challenge:

Both versions of the collections are licenced under a Creative Commons Attribution 4.0 International License.

Citation Information

If you use this in your work, please cite:

@article{McCann2018decaNLP,
  title={The Natural Language Decathlon: Multitask Learning as Question Answering},
  author={Bryan McCann and Nitish Shirish Keskar and Caiming Xiong and Richard Socher},
  journal={arXiv preprint arXiv:1806.08730},
  year={2018}
}

Contributions

Thanks to @thomwolf, @lewtun, @ghomasHudson, @lhoestq for adding this dataset.