esCorpius: A Massive Spanish Crawling Corpus

  Authors

Asier, Gutiérrez-Fandiño ; David, Pérez-Fernández ; Jordi, Armengol-Estapé ; David, Griol and Zoraida, Callejas

  Item identifier

http://hdl.handle.net/11372/LRT-4807

 Project URL

https://huggingface.co/datasets/LHF/escorpius

 Demo URL

https://huggingface.co/datasets/LHF/escorpius

 Referenced by

https://arxiv.org/pdf/2206.15147.pdf

 Date issued

2022-07-01

 Type

corpus, text

 Size

322.5 gb, 2421598201 sentences, 50040055322 tokens

 Language(s)

Spanish

 Description

In the recent years, Transformer-based models have lead to significant advances in language modelling for natural language processing. However, they require a vast amount of data to be (pre-)trained and there is a lack of corpora in languages other than English. Recently, several initiatives have presented multilingual datasets obtained from automatic web crawling. However, the results in Spanish present important shortcomings, as they are either too small in comparison with other languages, or present a low quality derived from sub-optimal cleaning and deduplication. In this paper, we introduce esCorpius, a Spanish crawling corpus obtained from near 1 Pb of Common Crawl data. It is the most extensive corpus in Spanish with this level of quality in the extraction, purification and deduplication of web textual content. Our data curation process involves a novel highly parallel cleaning pipeline and encompasses a series of deduplication mechanisms that together ensure the integrity of both document and paragraph boundaries. Additionally, we maintain both the source web page URL and the WARC shard origin URL in order to complain with EU regulations. esCorpius has been released under CC BY-NC-ND 4.0 license.

 Publisher

LHF Labs

 Subject(s)

spanish crawling corpus crawling corpus spanish corpus massive corpus large corpus clean deduplicated

 Collection(s)

LRT + Open Submissions Data & Tools

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