Datasets:

Sub-tasks:
extractive-qa
Languages:
English
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
crowdsourced
ArXiv:
Tags:
conversational-qa
License:
coqa / README.md
system's picture
system HF staff
Update files from the datasets library (from 1.4.0)
51ab127


Dataset Card for "coqa"

Table of Contents

Dataset Description

Dataset Summary

CoQA: A Conversational Question Answering Challenge

Supported Tasks

More Information Needed

Languages

More Information Needed

Dataset Structure

We show detailed information for up to 5 configurations of the dataset.

Data Instances

default

  • Size of downloaded dataset files: 55.40 MB
  • Size of the generated dataset: 18.35 MB
  • Total amount of disk used: 73.75 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 Sample Size

name train validation
default 7199 500

Dataset Creation

Curation Rationale

More Information Needed

Source Data

More Information Needed

Annotations

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{SivaAndAl:Coca,
       author = {Siva, Reddy and Danqi, Chen and  Christopher D., Manning},
        title = {WikiQA: A Challenge Dataset for Open-Domain Question Answering},
      journal = { arXiv},
         year = {2018},

}

Contributions

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