Learning and inference for clause identification

Xavier Carreras, Lluis Marques, Vasin Punyakanok, Dan Roth

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Citations (Scopus)

Abstract

This paper presents an approach to partial parsing of natural language sentences that makes global inference on top of the outcome of hierarchically learned local classifiers. The best decomposition of a sentence into clauses is chosen using a dynamic programming based scheme that takes into account previously identified partial solutions. This inference scheme applies learning at several levels-when identifying potential clauses and when scoring partial solutions. The classifiers are trained in a hierarchical fashion, building on previous classifications. The method presented significantly outperforms the best methods known so far for clause identification.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages35-47
Number of pages13
Volume2430
ISBN (Print)9783540440369
Publication statusPublished - 2002
Externally publishedYes
Event13th European Conference on Machine Learning, ECML 2002 - Helsinki, Finland
Duration: 19 Aug 200223 Aug 2002

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2430
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other13th European Conference on Machine Learning, ECML 2002
CountryFinland
CityHelsinki
Period19/8/0223/8/02

Fingerprint

Classifiers
Partial
Classifier
Dynamic programming
Parsing
Decomposition
Scoring
Natural Language
Dynamic Programming
Decompose
Learning

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Carreras, X., Marques, L., Punyakanok, V., & Roth, D. (2002). Learning and inference for clause identification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2430, pp. 35-47). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2430). Springer Verlag.

Learning and inference for clause identification. / Carreras, Xavier; Marques, Lluis; Punyakanok, Vasin; Roth, Dan.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 2430 Springer Verlag, 2002. p. 35-47 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 2430).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Carreras, X, Marques, L, Punyakanok, V & Roth, D 2002, Learning and inference for clause identification. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 2430, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 2430, Springer Verlag, pp. 35-47, 13th European Conference on Machine Learning, ECML 2002, Helsinki, Finland, 19/8/02.
Carreras X, Marques L, Punyakanok V, Roth D. Learning and inference for clause identification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 2430. Springer Verlag. 2002. p. 35-47. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Carreras, Xavier ; Marques, Lluis ; Punyakanok, Vasin ; Roth, Dan. / Learning and inference for clause identification. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 2430 Springer Verlag, 2002. pp. 35-47 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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