Graph-based named entity linking with Wikipedia
|Graph-based named entity linking with Wikipedia|
|Author(s)||Hachey B., Radford W., Curran J.R.|
|Published in||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Keyword(s)||entity resolution, integration, text mining, web intelligence, Wikipedia (Extra: entity resolution, Graph-based, Named entities, Text mining, Web intelligence, Wikipedia, Word-sense disambiguation, Wordnet, Information systems, Systems engineering, User interfaces, World Wide Web, Natural language processing systems)|
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Graph-based named entity linking with Wikipedia is a 2011 conference paper written in English by Hachey B., Radford W., Curran J.R. and published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
Named entity linking (NEL) grounds entity mentions to their corresponding Wikipedia article. State-of-the-art supervised NEL systems use features over the rich Wikipedia document and link-graph structure. Graph-based measures have been effective over WordNet for word sense disambiguation (wsd). We draw parallels between NEL and (wsd), motivating our unsupervised NEL approach that exploits the Wikipedia article and category link graphs. Our system achieves 85.5% accuracy on the TAC 2010 shared task - competitive with the best supervised and unsupervised systems.
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