Dataset Card for "xsum"

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:
• Repository: https://github.com/EdinburghNLP/XSum
• Paper: Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization
• Point of Contact: Shashi Narayan
• Size of downloaded dataset files: 257.30 MB
• Size of the generated dataset: 532.26 MB
• Total amount of disk used: 789.56 MB

Dataset Summary

Extreme Summarization (XSum) Dataset.

There are three features:

• document: Input news article.
• summary: One sentence summary of the article.
• id: BBC ID of the article.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

default

• Size of downloaded dataset files: 257.30 MB
• Size of the generated dataset: 532.26 MB
• Total amount of disk used: 789.56 MB

An example of 'validation' looks as follows.

{
    "document": "some-body",
    "id": "29750031",
    "summary": "some-sentence"
}

Data Fields

The data fields are the same among all splits.

default

• document: a string feature.
• summary: a string feature.
• id: a string feature.

Data Splits

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

@article{Narayan2018DontGM,
  title={Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization},
  author={Shashi Narayan and Shay B. Cohen and Mirella Lapata},
  journal={ArXiv},
  year={2018},
  volume={abs/1808.08745}
}

Contributions

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