annotations_creators:
- no-annotation
language_creators:
- found
language:
- ca
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- 10M<n<100M
source_datasets:
- original
- extended|opus_dogc
- extended|cawac
- extended|oscar
- extended|open_subtitles
- extended|wikipedia
- extended|projecte-aina/catalan_general_crawling
- extended|projecte-aina/catalan_government_crawling
task_categories:
- text-generation
task_ids:
- language-modeling
pretty_name: Catalan Textual Corpus
Dataset Card for Catalan Textual Corpus
Table of Contents
- Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://zenodo.org/record/4519349
- Paper: Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan
- Point of Contact: ona.degibert@bsc.es
Dataset Summary
The Catalan Textual Corpus is a 1760-million-token web corpus of Catalan built from several sources.
It consists of 1,758,388,896 tokens, 73,172,152 sentences, and 12,556,365 documents. Documents are separated by single new lines. These boundaries have been preserved as long as the license allowed it.
Supported Tasks and Leaderboards
This corpus is mainly intended to pretrain language models and word representations.
Languages
The dataset is in Catalan (ca-CA
).
Dataset Structure
Data Instances
{'text': "L'operatiu continuarà durant aquest divendres."}
Data Fields
text
(str): Text.
Data Splits
The dataset contains a single split: train
.
Dataset Creation
Curation Rationale
We created this corpus to contribute to the development of language models in Catalan, a low-resource language.
Source Data
Initial Data Collection and Normalization
The Catalan Textual Corpus is a 1760-million-token web corpus of Catalan built from several sources: existing corpora such as DOGC, CaWac (non-dedup version), Oscar (unshuffled version), Open Subtitles, Catalan Wikipedia, and three brand new crawlings: the Catalan General Crawling, obtained by crawling the 500 most popular .cat and .ad domains; the Catalan Government Crawling, obtained by crawling the .gencat domain and subdomains, belonging to the Catalan Government; and the ACN corpus with 220k news items from March 2015 until October 2020, crawled from the Catalan News Agency. For preprocessing we used Corpus-Cleaner, a modular Python-based toolkit to clean raw text corpora through generator pipelines.
Who are the source language producers?
The original data comes from various sources: existing corpora and crawlings from public websites.
Annotations
The dataset is unannotated.
Annotation process
[N/A]
Who are the annotators?
[N/A]
Personal and Sensitive Information
No anonymisation process was performed.
Considerations for Using the Data
Social Impact of Dataset
We hope this corpus contributes to the development of language models in Catalan, a low-resource language.
Discussion of Biases
We are aware that since the data comes from unreliable web pages and multilingual crawled corpora, some biases may be present in the dataset. Nonetheless, we have not applied any steps to reduce their impact.
Other Known Limitations
[N/A]
Additional Information
Dataset Curators
Ona de Gibert Bonet, Barcelona Supercomputing Center (ona.degibert@bsc.es)
This work was funded by the Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya within the framework of Projecte AINA.
Licensing Information
Creative Commons Attribution Share Alike 4.0 International.
Citation Information
@inproceedings{armengol-estape-etal-2021-multilingual,
title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
author = "Armengol-Estap{\'e}, Jordi and
Carrino, Casimiro Pio and
Rodriguez-Penagos, Carlos and
de Gibert Bonet, Ona and
Armentano-Oller, Carme and
Gonzalez-Agirre, Aitor and
Melero, Maite and
Villegas, Marta",
booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021",
month = aug,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.findings-acl.437",
doi = "10.18653/v1/2021.findings-acl.437",
pages = "4933--4946",
eprint={2107.07903},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Contributions
Thanks to @albertvillanova for adding this dataset.