Friday 19th of April 2024
 

Lexical Disambiguation in Natural Language Questions-NLQs



Question processing is a fundamental step in a question answering (QA) application, and its quality impacts the performance of QA application. The major challenging issue in processing question is how to extract semantic of natural language questions (NLQs). A human language is ambiguous. Ambiguity may occur at two levels; lexical and syntactic. In this paper, we propose a new approach for resolving lexical ambiguity problem by integrating context knowledge and concepts knowledge of a domain, into shallow natural language processing (SNLP) techniques. Concepts knowledge is modeled using ontology, while context knowledge is obtained from WordNet, and it is determined based on neighborhood words in a question. The approach will be applied to a university QA system.

Keywords: Question Answering (QA), Word Sense Disambiguation (WSD), Shallow Natural Language Processing (SNLP), WordNet, Context Knowledge, Ontology

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