TY - CHAP U1 - Konferenzveröffentlichung A1 - Abadji, Julien A1 - Ortiz Suárez, Pedro Javier A1 - Romary, Laurent A1 - Sagot, Benoît ED - Lüngen, Harald ED - Kupietz, Marc ED - Bański, Piotr ED - Barbaresi, Adrien ED - Clematide, Simon ED - Pisetta, Ines T1 - Ungoliant: An optimized pipeline for the generation of a very large-scale multilingual web corpus T2 - Proceedings of the Workshop on Challenges in the Management of Large Corpora (CMLC-9) 2021. Limerick, 12 July 2021 (Online-Event) N2 - Since the introduction of large language models in Natural Language Processing, large raw corpora have played a crucial role in Computational Linguistics. However, most of these large raw corpora are either available only for English or not available to the general public due to copyright issues. Nevertheless, there are some examples of freely available multilingual corpora for training Deep Learning NLP models, such as the OSCAR and Paracrawl corpora. However, they have quality issues, especially for low-resource languages. Moreover, recreating or updating these corpora is very complex. In this work, we try to reproduce and improve the goclassy pipeline used to create the OSCAR corpus. We propose a new pipeline that is faster, modular, parameterizable, and well documented. We use it to create a corpus similar to OSCAR but larger and based on recent data. Also, unlike OSCAR, the metadata information is at the document level. We release our pipeline under an open source license and publish the corpus under a research-only license. KW - Korpus KW - corpus linguistics KW - large corpora KW - Natürliche Sprache KW - Automatische Sprachanalyse KW - Computerlinguistik KW - Urheberrecht KW - Open Source Y1 - 2021 UN - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-104688 U6 - https://doi.org/10.14618/ids-pub-10468 DO - https://doi.org/10.14618/ids-pub-10468 SP - 1 EP - 9 PB - Leibniz-Institut für Deutsche Sprache CY - Mannheim ER -