SEACrowd/wikiann

Tasks

• named-entity-recognition

Citation text from the card

@inproceedings{pan-etal-2017-cross,
    title = "Cross-lingual Name Tagging and Linking for 282 Languages",
    author = "Pan, Xiaoman  and
      Zhang, Boliang  and
      May, Jonathan  and
      Nothman, Joel  and
      Knight, Kevin  and
      Ji, Heng",
    booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
    month = jul,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/P17-1178",
    doi = "10.18653/v1/P17-1178",
    pages = "1946--1958",
    abstract = "The ambitious goal of this work is to develop a cross-lingual name tagging and linking framework
    for 282 languages that exist in Wikipedia. Given a document in any of these languages, our framework is able
    to identify name mentions, assign a coarse-grained or fine-grained type to each mention, and link it to
    an English Knowledge Base (KB) if it is linkable. We achieve this goal by performing a series of
    new KB mining methods: generating {``}silver-standard{''} annotations by
    transferring annotations from English to other languages through cross-lingual links and KB properties,
    refining annotations through self-training and topic selection,
    deriving language-specific morphology features from anchor links, and mining word translation pairs from
    cross-lingual links. Both name tagging and linking results for 

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