Conference Proceedings

A semantics-enhanced language model for unsupervised word sense disambiguation

Shou-De Lin, Karin Verspoor, A Gelbukh (ed.)

Computational Linguistics and Intelligent Text Processing | SPRINGER-VERLAG BERLIN | Published : 2008

Abstract

An N-gram language model aims at capturing statistical word order dependency information from corpora. Although the concept of language models has been applied extensively to handle a variety of NLP problems with reasonable success, the standard model does not incorporate semantic information, and consequently limits its applicability to semantic problems such as word sense disambiguation. We propose a framework that integrates semantic information into the language model schema, allowing a system to exploit both syntactic and semantic information to address NLP problems. Furthermore, acknowledging the limited availability of semantically annotated data, we discuss how the proposed model can..

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