Inducing Sense-Discriminating Context Patterns from Sense-Tagged Corpora

Proceedings of the Fifth International Conference on Language Resources and Evaluation (LREC 2006)

Abstract

Traditionally, context features used in word sense disambiguation are based on collocation statistics and use only minimal syntactic and semantic information. Corpus Pattern Analysis is a technique for producing knowledge-rich context features that capture sense distinctions. It involves (1) identifying sense-carrying context patterns and using the derived context features to discriminate between the unseen instances. Both stages require manual seeding. In this paper, we show how to automate inducing sense-discriminating context features from a sense-tagged corpus.