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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