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Unsupervised induction of a syntax-semantics lexicon using iterative refinement

  • Columbia University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

We present a method for learning syntaxsemantics mappings for verbs from unannotated corpora. We learn linkings, i.e., mappings from the syntactic arguments and adjuncts of a verb to its semantic roles. By learning such linkings, we do not need to model individual semantic roles independently of one another, and we can exploit the relation between different mappings for the same verb, or between mappings for different verbs. We present an evaluation on a standard test set for semantic role labeling.

Original languageEnglish
Title of host publicationProceedings of the Main Conference and the Shared Task
PublisherAssociation for Computational Linguistics (ACL)
Pages180-188
Number of pages9
ISBN (Electronic)9781937284213
StatePublished - 2012
Event1st Joint Conference on Lexical and Computational Semantics, *SEM 2012 - Montreal, Canada
Duration: Jun 7 2012Jun 8 2012

Publication series

Name*SEM 2012 - 1st Joint Conference on Lexical and Computational Semantics
Volume1

Conference

Conference1st Joint Conference on Lexical and Computational Semantics, *SEM 2012
Country/TerritoryCanada
CityMontreal
Period06/7/1206/8/12

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