Datasets:
Tasks:
Summarization
Sub-tasks:
news-articles-summarization
Languages:
English
Size:
10K<n<100K
ArXiv:
License:
Dataset Card for "multi_news"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://github.com/Alex-Fabbri/Multi-News
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 245.06 MB
- Size of the generated dataset: 667.74 MB
- Total amount of disk used: 912.80 MB
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
Languages
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
: astring
feature.summary
: astring
feature.
Data Splits Sample Size
name | train | validation | test |
---|---|---|---|
default | 44972 | 5622 | 5622 |
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
@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.