Abstract
Precisely identifying entities is essential for semantic annotation. This paper addresses the problem of named entity disambiguation that aims at mapping entity mentions in a text onto the right entities in Wikipedia. The aim of this paper is to explore and evaluate various combinations of features extracted from Wikipedia and texts for the disambiguation task, based on a statistical ranking model of candidate entities. Through experiments, we show which combinations of features are the best choices for disambiguation.
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Nguyen, H.T., Cao, T.H. (2010). Exploring Wikipedia and Text Features for Named Entity Disambiguation. In: Nguyen, N.T., Le, M.T., Świątek, J. (eds) Intelligent Information and Database Systems. ACIIDS 2010. Lecture Notes in Computer Science(), vol 5991. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12101-2_2
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DOI: https://doi.org/10.1007/978-3-642-12101-2_2
Publisher Name: Springer, Berlin, Heidelberg
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