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A Candidate Generation Algorithm for Named Entities Disambiguation Using DBpedia

  • Wissem Bouarroudj
  • Zizette Boufaida
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 745)

Abstract

Word Sense Disambiguation (WSD) is the process of choosing one sense to an ambiguous word in a context. Ambiguity refers to the fact that a word can have different meanings. One form of the lexical ambiguity is polysemy (Apple is the company and eventually the fruit). The state-of-art approaches generally extract named entities (NE), generate candidate entities from a Knowledge Base (KB), and apply a comparison method to select the correct one. As a complement to the majority of those approaches which do not use the NE categories, we propose a disambiguation algorithm that uses those categories to reduce the number of the candidates. For instance, categories include person, location, organization, etc. we will show that considering them will considerably reduce the number of the resulting candidates. In this paper, we will focus on the step of generating the candidate entities from a KB, thus we will propose an algorithm that will use DBpedia to link NE categories to the values of rdf:type property. The obtained results are very promising.

Keywords

Linked Data Disambiguation Named entity Query processing Entity Linking 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.LIRE LaboratoryAbdelhamid Mehri Constantine 2 UniversityConstantineAlgeria

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