README.md

metadata

annotations_creators:
  - crowdsourced
language_creators:
  - found
language:
  - en
license:
  - other
multilinguality:
  - monolingual
size_categories:
  - 1K<n<10K
source_datasets:
  - extended|race
  - extended|cnn_dailymail
  - extended|wikipedia
  - extended|other
task_categories:
  - question-answering
task_ids:
  - extractive-qa
paperswithcode_id: coqa
pretty_name: 'CoQA: Conversational Question Answering Challenge'
tags:
  - conversational-qa
dataset_info:
  features:
    - name: source
      dtype: string
    - name: story
      dtype: string
    - name: questions
      sequence: string
    - name: answers
      sequence:
        - name: input_text
          dtype: string
        - name: answer_start
          dtype: int32
        - name: answer_end
          dtype: int32
  splits:
    - name: train
      num_bytes: 17953365
      num_examples: 7199
    - name: validation
      num_bytes: 1223427
      num_examples: 500
  download_size: 12187487
  dataset_size: 19176792
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*

Dataset Card for "coqa"

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://stanfordnlp.github.io/coqa/
• Repository: https://github.com/stanfordnlp/coqa-baselines
• Paper: CoQA: A Conversational Question Answering Challenge
• Point of Contact: Google Group, Siva Reddy, Danqi Chen
• Size of downloaded dataset files: 58.09 MB
• Size of the generated dataset: 19.24 MB
• Total amount of disk used: 77.33 MB

Dataset Summary

CoQA is a large-scale dataset for building Conversational Question Answering systems.

Our dataset contains 127k questions with answers, obtained from 8k conversations about text passages from seven diverse domains. The questions are conversational, and the answers are free-form text with their corresponding evidence highlighted in the passage.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

• Size of downloaded dataset files: 58.09 MB
• Size of the generated dataset: 19.24 MB
• Total amount of disk used: 77.33 MB

An example of 'train' looks as follows.

This example was too long and was cropped:

{
    "answers": "{\"answer_end\": [179, 494, 511, 545, 879, 1127, 1128, 94, 150, 412, 1009, 1046, 643, -1, 764, 724, 125, 1384, 881, 910], \"answer_...",
    "questions": "[\"When was the Vat formally opened?\", \"what is the library for?\", \"for what subjects?\", \"and?\", \"what was started in 2014?\", \"ho...",
    "source": "wikipedia",
    "story": "\"The Vatican Apostolic Library (), more commonly called the Vatican Library or simply the Vat, is the library of the Holy See, l..."
}

Data Fields

The data fields are the same among all splits.

default

• source: a string feature.
• story: a string feature.
• questions: a list of string features.
• answers: a dictionary feature containing:
  • input_text: a string feature.
  • answer_start: a int32 feature.
  • answer_end: a int32 feature.

Data Splits

name	train	validation
default	7199	500

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

CoQA contains passages from seven domains. We make five of these public under the following licenses:

• Literature and Wikipedia passages are shared under CC BY-SA 4.0 license.
• Children's stories are collected from MCTest which comes with MSR-LA license.
• Middle/High school exam passages are collected from RACE which comes with its own license.
• News passages are collected from the DeepMind CNN dataset which comes with Apache license.

Citation Information

@article{reddy-etal-2019-coqa,
    title = "{C}o{QA}: A Conversational Question Answering Challenge",
    author = "Reddy, Siva  and
      Chen, Danqi  and
      Manning, Christopher D.",
    journal = "Transactions of the Association for Computational Linguistics",
    volume = "7",
    year = "2019",
    address = "Cambridge, MA",
    publisher = "MIT Press",
    url = "https://aclanthology.org/Q19-1016",
    doi = "10.1162/tacl_a_00266",
    pages = "249--266",
}

Contributions

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