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1
Towards a Cleaner Document-Oriented Multilingual Crawled Corpus
In: https://hal.inria.fr/hal-03536361 ; 2022 (2022)
Abstract: 12 pages, 6 figures, 2 tables ; The need for raw large raw corpora has dramatically increased in recent years with the introduction of transfer learning and semi-supervised learning methods to Natural Language Processing. And while there have been some recent attempts to manually curate the amount of data necessary to train large language models, the main way to obtain this data is still through automatic web crawling. In this paper we take the existing multilingual web corpus OSCAR and its pipeline Ungoliant that extracts and classifies data from Common Crawl at the line level, and propose a set of improvements and automatic annotations in order to produce a new document-oriented version of OSCAR that could prove more suitable to pre-train large generative language models as well as hopefully other applications in Natural Language Processing and Digital Humanities.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; Common Crawl; Language Modeling; Web corpus
URL: https://hal.inria.fr/hal-03536361
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Towards a Cleaner Document-Oriented Multilingual Crawled Corpus ...
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Ungoliant: An Optimized Pipeline for the Generation of a Very Large-Scale Multilingual Web Corpus
In: CMLC 2021 - 9th Workshop on Challenges in the Management of Large Corpora ; https://hal.inria.fr/hal-03301590 ; CMLC 2021 - 9th Workshop on Challenges in the Management of Large Corpora, Jul 2021, Limerick / Virtual, Ireland. ⟨10.14618/ids-pub-10468⟩ ; https://www.cl2021.org/ (2021)
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4
Ungoliant: An optimized pipeline for the generation of a very large-scale multilingual web corpus ...
Abadji, Julien; Ortiz Suárez, Pedro Javier; Romary, Laurent. - : Leibniz-Institut für Deutsche Sprache, 2021
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5
Ungoliant: An optimized pipeline for the generation of a very large-scale multilingual web corpus [Online resource]
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