Please use this identifier to cite or link to this item: http://hdl.handle.net/10525/1591

 Title: Cultural Knowledge for Named Entity Disambiguation: A Graph-Based Semantic Relatedness Approach Authors: Lisa Gentile, AnnaZhang, ZiqiXia, LeiIria, José Keywords: WikipediaNamed Entity DisambiguationSemantic RelatednessGraph Issue Date: 2010 Publisher: Institute of Mathematics and Informatics Bulgarian Academy of Sciences Citation: Serdica Journal of Computing, Vol. 4, No 2, (2010), 217p-242p Abstract: One of the ultimate aims of Natural Language Processing is to automate the analysis of the meaning of text. A fundamental step in that direction consists in enabling effective ways to automatically link textual references to their referents, that is, real world objects. The work presented in this paper addresses the problem of attributing a sense to proper names in a given text, i.e., automatically associating words representing Named Entities with their referents. The method for Named Entity Disambiguation proposed here is based on the concept of semantic relatedness, which in this work is obtained via a graph-based model over Wikipedia. We show that, without building the traditional bag of words representation of the text, but instead only considering named entities within the text, the proposed method achieves results competitive with the state-of-the-art on two different datasets. URI: http://hdl.handle.net/10525/1591 ISSN: 1312-6555 Appears in Collections: Volume 4 Number 2

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