2 datasets found
  1. h

    universal_ner

    • huggingface.co
    Updated Sep 3, 2024
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    Universal NER (2024). universal_ner [Dataset]. https://huggingface.co/datasets/universalner/universal_ner
    Explore at:
    Dataset updated
    Sep 3, 2024
    Dataset authored and provided by
    Universal NER
    License

    Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
    License information was derived automatically

    Description

    Universal Named Entity Recognition (UNER) aims to fill a gap in multilingual NLP: high quality NER datasets in many languages with a shared tagset.

    UNER is modeled after the Universal Dependencies project, in that it is intended to be a large community annotation effort with language-universal guidelines. Further, we use the same text corpora as Universal Dependencies.

  2. h

    universal_ner_nordic_FL

    • huggingface.co
    Updated Nov 14, 2024
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    Kätriin Kukk (2024). universal_ner_nordic_FL [Dataset]. https://huggingface.co/datasets/K2triinK/universal_ner_nordic_FL
    Explore at:
    Dataset updated
    Nov 14, 2024
    Authors
    Kätriin Kukk
    Description

    Universal Named Entity Recognition (UNER) aims to fill a gap in multilingual NLP: high quality NER datasets in many languages with a shared tagset. UNER is modeled after the Universal Dependencies project, in that it is intended to be a large community annotation effort with language-universal guidelines. Further, we use the same text corpora as Universal Dependencies.

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Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Universal NER (2024). universal_ner [Dataset]. https://huggingface.co/datasets/universalner/universal_ner

universal_ner

universalner/universal_ner

Explore at:
Dataset updated
Sep 3, 2024
Dataset authored and provided by
Universal NER
License

Attribution-ShareAlike 4.0 (CC BY-SA 4.0)https://creativecommons.org/licenses/by-sa/4.0/
License information was derived automatically

Description

Universal Named Entity Recognition (UNER) aims to fill a gap in multilingual NLP: high quality NER datasets in many languages with a shared tagset.

UNER is modeled after the Universal Dependencies project, in that it is intended to be a large community annotation effort with language-universal guidelines. Further, we use the same text corpora as Universal Dependencies.

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