Dataset Card for "DACSA"

Dataset Summary

The Dataset for Automatic summarization of Catalan and Spanish newspaper Articles (DACSA) corpus. It is a high-quality large-scale corpus that can be used to train summarization models for Catalan and Spanish. The data provides pairs of news article and its summary from different newspapers for both, the Catalan and the Spanish languages. Regarding the Catalan set, there are 725,184 sample pairs from 9 newspapers, regarding the Spanish set, the corpus provides 2,120,649 sample pairs from 21 newspapers.

Supported Tasks and Leaderboards

More information needed

Languages

• catalan
• spanish

Dataset Structure

Data Fields

• 'id': A string representing the article ID.
• 'summary': A string containing the article summary.
• 'article' : A string containing the article text.

Data Splits

Four splits are provided for each language set

• train: samples for training models
• validation: samples for adjusting and validating models
• test.i: test samples from newspapers present in train and validation splits
• test.ni: test samples from newspapers not present in training and validation splits

The validation and test-i splits contain a uniform distribution of samples from each newspaper source.

Languages	ISO 639-1 Code	Train	Val	Test.i	Test.ni	Total
Catalan	ca	636596	35376	35376	17836	725184
Spanish	es	1802919	104052	104052	109626	2120649

Dataset Creation

Curation Rationale

More information needed

Source Data

Newspapers from Spain that publish news in Catalan or Spanish

Initial Data Collection and Normalization

Detailed in the paper

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

These data are released under this licensing scheme. We do not own any of the text from which these data has been extracted.

This DACSA dataset package is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/

Should you consider that our data contains material that is owned by you and should therefore not be reproduced here, please:

• Clearly identify yourself, with detailed contact data such as an address, telephone number or email address at which you can be contacted.
• Clearly identify the copyrighted work claimed to be infringed.
• Clearly identify the material that is claimed to be infringing and information reasonably sufficient to allow us to locate the material. We will comply to legitimate requests by removing the affected sources from the next release of the corpus.

Citation Information

If you use any of the datasets, models or code modules, please cite the following paper:

@inproceedings{segarra-soriano-etal-2022-dacsa,
    title = "{DACSA}: A large-scale Dataset for Automatic summarization of {C}atalan and {S}panish newspaper Articles",
    author = "Segarra Soriano, Encarnaci{\'o}n  and
      Ahuir, Vicent  and
      Hurtado, Llu{\'\i}s-F.  and
      Gonz{\'a}lez, Jos{\'e}",
    booktitle = "Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
    month = jul,
    year = "2022",
    address = "Seattle, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.naacl-main.434",
    doi = "10.18653/v1/2022.naacl-main.434",
    pages = "5931--5943",
    abstract = "The application of supervised methods to automatic summarization requires the availability of adequate corpora consisting of a set of document-summary pairs. As in most Natural Language Processing tasks, the great majority of available datasets for summarization are in English, making it difficult to develop automatic summarization models for other languages. Although Spanish is gradually forming part of some recent summarization corpora, it is not the same for minority languages such as Catalan.In this work, we describe the construction of a corpus of Catalan and Spanish newspapers, the Dataset for Automatic summarization of Catalan and Spanish newspaper Articles (DACSA) corpus. It is a high-quality large-scale corpus that can be used to train summarization models for Catalan and Spanish.We have carried out an analysis of the corpus, both in terms of the style of the summaries and the difficulty of the summarization task. In particular, we have used a set of well-known metrics in the summarization field in order to characterize the corpus. Additionally, for benchmarking purposes, we have evaluated the performances of some extractive and abstractive summarization systems on the DACSA corpus.",
}