Data processing: speech signal processing – linguistics – language – Linguistics – Natural language
Reexamination Certificate
2004-11-18
2010-10-12
Hudspeth, David R (Department: 2626)
Data processing: speech signal processing, linguistics, language
Linguistics
Natural language
C704S001000, C704S010000
Reexamination Certificate
active
07813916
ABSTRACT:
Coreference resolution is the process of identifying when two noun phrases (NP) refer to the same entity. Two main contributions to computational coreference resolution are made. First, this work contributes a new method for recognizing when an NP is anaphoric. Second, traditional approaches to coreference resolution typically select the most appropriate antecedent by recognizing word similarity, proximity, and agreement in number, gender, and semantic class. This work contributes a new source of evidence that focuses on the roles that an anaphor and antecedent play in particular events or relationships. I show that using contextual role knowledge as part of the coreference resolution process increases the number of anaphors that can be resolved, and I demonstrate an unsupervised method for acquiring contextual role knowledge that does not require an annotated training corpus. A probabilistic model based on the Dempster-Shafer model of evidence is used to incorporate contextual role knowledge with traditional evidence sources.
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Hudspeth David R
Spooner Lamont M
University of Utah
Workman Nydegger
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