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Word sense disambiguation using implicit information

Published online by Cambridge University Press:  13 September 2019

Goonjan Jain  and
D.K. Lobiyal
Goonjan Jain*
Affiliation:
Department of Applied Mathematics, Delhi Technological University, New Delhi110042, India
D.K. Lobiyal
Affiliation:
School of Computer and Systems Sciences, Jawaharlal Nehru University, New Delhi110067, India
*
*Corresponding author. Email: goonjan_jain@hotmail.com
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Abstract

Humans proficiently interpret the true sense of an ambiguous word by establishing association among words in a sentence. The complete sense of text is also based on implicit information, which is not explicitly mentioned. The absence of this implicit information is a significant problem for a computer program that attempts to determine the correct sense of ambiguous words. In this paper, we propose a novel method to uncover the implicit information that links the words of a sentence. We reveal this implicit information using a graph, which is then used to disambiguate the ambiguous word. The experiments show that the proposed algorithm interprets the correct sense for both homonyms and polysemous words. Our proposed algorithm has performed better than the approaches presented in the SemEval-2013 task for word sense disambiguation and has shown an accuracy of 79.6 percent, which is 2.5 percent better than the best unsupervised approach in SemEval-2007.

Keywords

Word sense disambiguationCommon senseConceptNetImplicit informationLexical priming
Type
Article
Information
Natural Language Engineering , Volume 26 , Issue 4 , July 2020 , pp. 413 - 432
Copyright
© Cambridge University Press 2019

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