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Inducing Sense-Discriminating Context Patterns from Sense-Tagged Corpora
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Inducing Sense-Discriminating Context Patterns from Sense-Tagged Corpora
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.
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