The Use of Word Sense Disambiguation in an Information Extraction System

Abstract

This paper describes a rule-based methodology for word sense disambiguation and an application of the methodology to information extraction using rules generalized with the help of the WordNet system. The methodology creates word sense disambiguation rules based on user trained examples working in the domain of interest. It achieves accuracy rates comparable to the best competing methods and can be easily integrated into higher level applications. Introduction Most information extraction (IE) systems have used hand-crafted semantic resources for each application domain, or have employed techniques for automatically or semi-automatically constructing lexicons of annotated texts in the domain (Riloff & Lehnert 1993) (Riloff 1996) (Krupka 1995). Few examples apply general lexical semantic resources. NYU's MUC-4 system (Grishman, Macleod, & Sterling 1992) made some attempt at using WordNet for semantic classification. However, they ran into the problem of automated sense disambiguation b...