GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages

Abstract

The need for large text corpora has increased with the advent of pretrained language models and, in particular, the discovery of scaling laws for these models. Most available corpora have sufficient data only for languages with large dominant communities. However, there is no corpus available that (i) covers a wide range of minority languages; (ii) is generated by an open-source reproducible pipeline; and (iii) is rigorously cleaned from noise, making it trustworthy to use. We present GlotCC, a clean, document-level, 2TB general domain corpus derived from CommonCrawl, covering more than 1000 languages. We make GlotCC and the system used to generate it— including the pipeline, language identification model, and filters—available to the research community.Corpus v. 1.0 https://huggingface.co/datasets/cis-lmu/GlotCC-v1Pipeline v. 3.0 https://github.com/cisnlp/GlotCC

Cite

Text

Kargaran et al. "GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages." Neural Information Processing Systems, 2024. doi:10.52202/079017-0540

Markdown

[Kargaran et al. "GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages." Neural Information Processing Systems, 2024.](https://mlanthology.org/neurips/2024/kargaran2024neurips-glotcc/) doi:10.52202/079017-0540

BibTeX

@inproceedings{kargaran2024neurips-glotcc,
  title     = {{GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages}},
  author    = {Kargaran, Amir Hossein and Yvon, François and Schütze, Hinrich},
  booktitle = {Neural Information Processing Systems},
  year      = {2024},
  doi       = {10.52202/079017-0540},
  url       = {https://mlanthology.org/neurips/2024/kargaran2024neurips-glotcc/}
}