SGER: Exploratory Research of Word Sense Disambiguation Methods for All Words in Open Text

University Of North Texas, Denton TX

Investigators

Abstract

Word Sense Disambiguation (WSD) is a core task in natural language processing and is considered essential for major applications like text understanding, common sense reasoning, and machine translation. Previous research on WSD has produced good disambiguation schemes for the relatively few words for which training data has been available. In contrast, there have been few attempts to create systems that disambiguate all words in open text. The goal of this one-year project is to conduct exploratory research of various WSD techniques to enable the development of a tool for semantic tagging of all words in open text. The methods to be investigated rely on inner and outer representations of word sense. The inner representation comes from examples of word meanings; whereas, the outer representation is given by semantic relations between word senses. These two representations correspond to two different views on word meanings that can be used to derive complementary WSD techniques, which ultimately can be combined, yielding a tool for resolving the semantic ambiguity of all words in open text. The techniques developed as part of this project are expected to significantly improve the performance level of WSD applications for open text and should have an impact on other important applications in natural language processing.