multi_news / README.md
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paperswithcode_id: multi-news

Dataset Card for "multi_news"

Table of Contents

Dataset Description

Dataset Summary

Multi-News, consists of news articles and human-written summaries of these articles from the site newser.com. Each summary is professionally written by editors and includes links to the original articles cited.

There are two features:

  • document: text of news articles seperated by special token "|||||".
  • summary: news summary.

Supported Tasks and Leaderboards

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: 245.06 MB
  • Size of the generated dataset: 667.74 MB
  • Total amount of disk used: 912.80 MB

An example of 'validation' looks as follows.

{
    "document": "some line val \n another line",
    "summary": "target val line"
}

Data Fields

The data fields are the same among all splits.

default

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

Data Splits

name train validation test
default 44972 5622 5622

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


@misc{alex2019multinews,
    title={Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model},
    author={Alexander R. Fabbri and Irene Li and Tianwei She and Suyi Li and Dragomir R. Radev},
    year={2019},
    eprint={1906.01749},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}

Contributions

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