@article{chisholm-hachey-2015-entity,
    title = "Entity Disambiguation with Web Links",
    author = "Chisholm, Andrew  and
      Hachey, Ben",
    editor = "Collins, Michael  and
      Lee, Lillian",
    journal = "Transactions of the Association for Computational Linguistics",
    volume = "3",
    year = "2015",
    address = "Cambridge, MA",
    publisher = "MIT Press",
    url = "https://aclanthology.org/Q15-1011/",
    doi = "10.1162/tacl_a_00129",
    pages = "145--156",
    abstract = "Entity disambiguation with Wikipedia relies on structured information from redirect pages, article text, inter-article links, and categories. We explore whether web links can replace a curated encyclopaedia, obtaining entity prior, name, context, and coherence models from a corpus of web pages with links to Wikipedia. Experiments compare web link models to Wikipedia models on well-known conll and tac data sets. Results show that using 34 million web links approaches Wikipedia performance. Combining web link and Wikipedia models produces the best-known disambiguation accuracy of 88.7 on standard newswire test data."
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    <abstract>Entity disambiguation with Wikipedia relies on structured information from redirect pages, article text, inter-article links, and categories. We explore whether web links can replace a curated encyclopaedia, obtaining entity prior, name, context, and coherence models from a corpus of web pages with links to Wikipedia. Experiments compare web link models to Wikipedia models on well-known conll and tac data sets. Results show that using 34 million web links approaches Wikipedia performance. Combining web link and Wikipedia models produces the best-known disambiguation accuracy of 88.7 on standard newswire test data.</abstract>
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%0 Journal Article
%T Entity Disambiguation with Web Links
%A Chisholm, Andrew
%A Hachey, Ben
%J Transactions of the Association for Computational Linguistics
%D 2015
%V 3
%I MIT Press
%C Cambridge, MA
%F chisholm-hachey-2015-entity
%X Entity disambiguation with Wikipedia relies on structured information from redirect pages, article text, inter-article links, and categories. We explore whether web links can replace a curated encyclopaedia, obtaining entity prior, name, context, and coherence models from a corpus of web pages with links to Wikipedia. Experiments compare web link models to Wikipedia models on well-known conll and tac data sets. Results show that using 34 million web links approaches Wikipedia performance. Combining web link and Wikipedia models produces the best-known disambiguation accuracy of 88.7 on standard newswire test data.
%R 10.1162/tacl_a_00129
%U https://aclanthology.org/Q15-1011/
%U https://doi.org/10.1162/tacl_a_00129
%P 145-156
Markdown (Informal)
[Entity Disambiguation with Web Links](https://aclanthology.org/Q15-1011/) (Chisholm & Hachey, TACL 2015)
ACL