annotations_creators:
- found
language_creators:
- found
languages:
- de
- es
- fr
- ru
- tr
licenses:
- other-research-only
multilinguality:
- multilingual
size_categories:
de:
- 100K<n<1M
es:
- 100K<n<1M
fr:
- 100K<n<1M
ru:
- 10K<n<100K
tu:
- 100K<n<1M
source_datasets:
- extended|cnn_dailymail
- original
task_categories:
- conditional-text-generation
- text-classification
task_ids:
- machine-translation
- multi-class-classification
- multi-label-classification
- summarization
- topic-classification
paperswithcode_id: mlsum
pretty_name: MLSUM
Dataset Card for MLSUM
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage:
- Repository: https://github.com/recitalAI/MLSUM
- Paper: https://www.aclweb.org/anthology/2020.emnlp-main.647/
- Point of Contact: email
- Size of downloaded dataset files: 1748.64 MB
- Size of the generated dataset: 4635.42 MB
- Total amount of disk used: 6384.06 MB
Dataset Summary
We present MLSUM, the first large-scale MultiLingual SUMmarization dataset. Obtained from online newspapers, it contains 1.5M+ article/summary pairs in five different languages -- namely, French, German, Spanish, Russian, Turkish. Together with English newspapers from the popular CNN/Daily mail dataset, the collected data form a large scale multilingual dataset which can enable new research directions for the text summarization community. We report cross-lingual comparative analyses based on state-of-the-art systems. These highlight existing biases which motivate the use of a multi-lingual dataset.
Supported Tasks and Leaderboards
Languages
Dataset Structure
We show detailed information for up to 5 configurations of the dataset.
Data Instances
de
- Size of downloaded dataset files: 330.52 MB
- Size of the generated dataset: 897.34 MB
- Total amount of disk used: 1227.86 MB
An example of 'validation' looks as follows.
{
"date": "01/01/2001",
"summary": "A text",
"text": "This is a text",
"title": "A sample",
"topic": "football",
"url": "https://www.google.com"
}
es
- Size of downloaded dataset files: 489.53 MB
- Size of the generated dataset: 1274.55 MB
- Total amount of disk used: 1764.09 MB
An example of 'validation' looks as follows.
{
"date": "01/01/2001",
"summary": "A text",
"text": "This is a text",
"title": "A sample",
"topic": "football",
"url": "https://www.google.com"
}
fr
- Size of downloaded dataset files: 591.27 MB
- Size of the generated dataset: 1537.36 MB
- Total amount of disk used: 2128.63 MB
An example of 'validation' looks as follows.
{
"date": "01/01/2001",
"summary": "A text",
"text": "This is a text",
"title": "A sample",
"topic": "football",
"url": "https://www.google.com"
}
ru
- Size of downloaded dataset files: 101.30 MB
- Size of the generated dataset: 263.38 MB
- Total amount of disk used: 364.68 MB
An example of 'train' looks as follows.
{
"date": "01/01/2001",
"summary": "A text",
"text": "This is a text",
"title": "A sample",
"topic": "football",
"url": "https://www.google.com"
}
tu
- Size of downloaded dataset files: 236.03 MB
- Size of the generated dataset: 662.79 MB
- Total amount of disk used: 898.82 MB
An example of 'train' looks as follows.
{
"date": "01/01/2001",
"summary": "A text",
"text": "This is a text",
"title": "A sample",
"topic": "football",
"url": "https://www.google.com"
}
Data Fields
The data fields are the same among all splits.
de
text
: astring
feature.summary
: astring
feature.topic
: astring
feature.url
: astring
feature.title
: astring
feature.date
: astring
feature.
es
text
: astring
feature.summary
: astring
feature.topic
: astring
feature.url
: astring
feature.title
: astring
feature.date
: astring
feature.
fr
text
: astring
feature.summary
: astring
feature.topic
: astring
feature.url
: astring
feature.title
: astring
feature.date
: astring
feature.
ru
text
: astring
feature.summary
: astring
feature.topic
: astring
feature.url
: astring
feature.title
: astring
feature.date
: astring
feature.
tu
text
: astring
feature.summary
: astring
feature.topic
: astring
feature.url
: astring
feature.title
: astring
feature.date
: astring
feature.
Data Splits
name | train | validation | test |
---|---|---|---|
de | 220887 | 11394 | 10701 |
es | 266367 | 10358 | 13920 |
fr | 392902 | 16059 | 15828 |
ru | 25556 | 750 | 757 |
tu | 249277 | 11565 | 12775 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
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
Usage of dataset is restricted to non-commercial research purposes only. Copyright belongs to the original copyright holders. See https://github.com/recitalAI/MLSUM#mlsum
Citation Information
@article{scialom2020mlsum,
title={MLSUM: The Multilingual Summarization Corpus},
author={Scialom, Thomas and Dray, Paul-Alexis and Lamprier, Sylvain and Piwowarski, Benjamin and Staiano, Jacopo},
journal={arXiv preprint arXiv:2004.14900},
year={2020}
}
Contributions
Thanks to @RachelKer, @albertvillanova, @thomwolf for adding this dataset.