kopi_cc

KoPI-CC (Korpus Perayapan Indonesia)-CC is Indonesian Only Extract from Common Crawl snapshots ,each snapshots get extracted using ungoliant and get extra "filtering" using deduplication technique

Dataset Usage

Run pip install nusacrowd before loading the dataset through HuggingFace's load_dataset.

Citation

@ARTICLE{2022arXiv220106642A,
       author = {{Abadji}, Julien and {Ortiz Suarez}, Pedro and {Romary}, Laurent and {Sagot}, Benoit},
        title = "{Towards a Cleaner Document-Oriented Multilingual Crawled Corpus}",
      journal = {arXiv e-prints},
     keywords = {Computer Science - Computation and Language},
         year = 2022,
        month = jan,
          eid = {arXiv:2201.06642},
        pages = {arXiv:2201.06642},
archivePrefix = {arXiv},
       eprint = {2201.06642},
 primaryClass = {cs.CL},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2022arXiv220106642A},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
@inproceedings{AbadjiOrtizSuarezRomaryetal.2021,
  author    = {Julien Abadji and Pedro Javier Ortiz Su{'a}rez and Laurent Romary and Benoit Sagot},
  title     = {Ungoliant: An optimized pipeline for the generation of a very large-scale multilingual web corpus},
  series = {Proceedings of the Workshop on Challenges in the Management of Large Corpora (CMLC-9) 2021. Limerick, 12 July 2021 (Online-Event)},
  editor    = {Harald L{"u}ngen and Marc Kupietz and Piotr Bański and Adrien Barbaresi and Simon Clematide and Ines Pisetta},
  publisher = {Leibniz-Institut f{"u}r Deutsche Sprache},
  address   = {Mannheim},
  doi       = {10.14618/ids-pub-10468},
  url       = {https://nbn-resolving.org/urn:nbn:de:bsz:mh39-104688},
  pages     = {1 -- 9},
  year      = {2021},
  abstract  = {Since the introduction of large language models in Natural Language Processing, large raw corpora have played a crucial role in Computational Linguistics.},
  language  = {en}
}

License

CC0

Homepage

https://huggingface.co/datasets/munggok/KoPI-CC

NusaCatalogue

For easy indexing and metadata: https://indonlp.github.io/nusa-catalogue