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bltlab/open-ner-core-types

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Permissive or share-alike

The declared licence (cc-by-4.0) is classified as permissive.

Declared licence: cc-by-4.0, from the tagEvidence: README.md at 8391e6d
Licence files: No licence file at the top level of the repositoryEvidence: file list at 8391e6d
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

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Tasks

token-classification

Citation text from the card

@inproceedings{palen-michel-etal-2025-openner,
    title = "{O}pen{NER} 1.0: Standardized Open-Access Named Entity Recognition Datasets in 50+ Languages",
    author = {Palen-Michel, Chester  and
      Pickering, Maxwell  and
      Kruse, Maya  and
      S{\"a}lev{\"a}, Jonne  and
      Lignos, Constantine},
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.emnlp-main.1708/",
    doi = "10.18653/v1/2025.emnlp-main.1708",
    pages = "33637--33662",
    ISBN = "979-8-89176-332-6",
    abstract = "We present OpenNER 1.0, a standardized collection of openly-available named entity recognition (NER) datasets.OpenNER contains 36 NER corpora that span 52 languages, human-annotated in varying named entity ontologies.We correct annotation format issues, standardize the original datasets into a uniform representation with consistent entity type names across corpora, and provide the collection in a structure that enables research in multilingual and multi-ontology NER.We provide baseline results using three pretrained multilingual language models and two large language models to compare the performance of recent models and facilitate future re

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dataset_licence({ "id": "bltlab/open-ner-core-types" })
signal: "permissive"
stated_licence: "cc-by-4.0"
sources: 0