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Author Rumshisky, Anna ♦ Pustejovsky, James
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Sense-tagged Corpus ♦ Sense-discriminating Context Pattern ♦ Context Feature ♦ Knowledge-rich Context Feature ♦ Sense-carrying Context Pattern ♦ Unseen Instance ♦ Sense Distinction ♦ Sense-discriminating Context Feature ♦ Manual Seeding ♦ Collocation Statistic ♦ Semantic Information ♦ Corpus Pattern Analysis ♦ Word Sense Disambiguation
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 (2) 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. 1.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Publisher Date 2006-01-01