README.md

metadata

language:
  - en
paperswithcode_id: quarel
pretty_name: QuaRel
dataset_info:
  features:
    - name: id
      dtype: string
    - name: answer_index
      dtype: int32
    - name: logical_forms
      sequence: string
    - name: logical_form_pretty
      dtype: string
    - name: world_literals
      sequence:
        - name: world1
          dtype: string
        - name: world2
          dtype: string
    - name: question
      dtype: string
  splits:
    - name: train
      num_bytes: 1072874
      num_examples: 1941
    - name: test
      num_bytes: 307588
      num_examples: 552
    - name: validation
      num_bytes: 154308
      num_examples: 278
  download_size: 631370
  dataset_size: 1534770

Dataset Card for "quarel"

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: https://allenai.org/data/quarel
• Repository: More Information Needed
• Paper: More Information Needed
• Point of Contact: More Information Needed
• Size of downloaded dataset files: 0.63 MB
• Size of the generated dataset: 1.53 MB
• Total amount of disk used: 2.17 MB

Dataset Summary

QuaRel is a crowdsourced dataset of 2771 multiple-choice story questions, including their logical forms.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

• Size of downloaded dataset files: 0.63 MB
• Size of the generated dataset: 1.53 MB
• Total amount of disk used: 2.17 MB

An example of 'train' looks as follows.

{
    "answer_index": 0,
    "id": "QuaRel_V1_B5_1403",
    "logical_form_pretty": "qrel(time, lower, world1) -> qrel(distance, higher, world2) ; qrel(distance, higher, world1)",
    "logical_forms": ["(infer (time lower world1) (distance higher world2) (distance higher world1))", "(infer (time lower world2) (distance higher world1) (distance higher world2))"],
    "question": "John and Rita are going for a run.  Rita gets tired and takes a break on the park bench.  After twenty minutes in the park, who has run farther? (A) John (B) Rita",
    "world_literals": {
        "world1": ["Rita"],
        "world2": ["John"]
    }
}

Data Fields

The data fields are the same among all splits.

default

• id: a string feature.
• answer_index: a int32 feature.
• logical_forms: a list of string features.
• logical_form_pretty: a string feature.
• world_literals: a dictionary feature containing:
  • world1: a string feature.
  • world2: a string feature.
• question: a string feature.

Data Splits

name	train	validation	test
default	1941	278	552

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

More Information Needed

Citation Information

@inproceedings{quarel_v1,
    title={QuaRel: A Dataset and Models for Answering Questions about Qualitative Relationships},
    author={Oyvind Tafjord, Peter Clark, Matt Gardner, Wen-tau Yih, Ashish Sabharwal},
    year={2018},
    journal={arXiv:1805.05377v1}
}

Contributions

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