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Learning Constraint Grammar-style disambiguation rules using inductive logic programming

Published: 10 August 1998 Publication History

Abstract

This paper reports a pilot study, in which Constraint Grammar inspired rules were learnt using the Progol machine-learning system. Rules discarding faulty readings of ambiguously tagged words were learnt for the part of speech tags of the Stockholm-Umeå Corpus. Several thousand disambiguation rules were induced. When tested on unseen data, 98% of the words retained the correct reading after tagging. However, there were ambiguities pending after tagging, on an average 1.13 tags per word. The results suggest that the Progol system can be useful for learning tagging rules of good quality.

References

[1]
Eric Brill. 1994. Some advances in transformation-based part of speech tagging. In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94).
[2]
James Cussens. 1997. Part of speech tagging using Progol. In Proceedings of the 7th International Workshop on Inductive Logic Programming (ILP-97), pages 93--108.
[3]
Martin Eineborg and Nikolaj Lindberg. 1998. Induction of Constraint Grammar-rules using Progol. In Proceedings of The Eighth International Conference on Inductive Logic Programming (ILP'98), Madison, Wisconsin.
[4]
Eva Ejerhed, Gunnel Källgren, Wennstedt Ola, and Magnus Åström. 1992. The Linguistic Annotation System of the Stockholm-Umeå Project. Department of General Linguistics, University of Umeå.
[5]
Fred Karlsson, Atro Voutilainen, Juha Heikkilä, and Arto Anttila, editors. 1995. Constraint Grammar: A language-independent system for parsing unrestricted text. Mouton de Gruyter, Berlin and New York.
[6]
Oliver Manson, 1997. QTAG---A portable probabilistic tagger. Corpus Research, The University of Birmingham, U.K.
[7]
Stephen Muggleton. 1995. Inverse entailment and Progol. New Generation Computing Journal, 13: 245--286.
[8]
Daniel Ridings. 1998. SUC and the Brill tagger. GU-ISS-98-1 (Research Reports from the Department of Swedish, Göteborg University).
[9]
Sam Roberts, 1997. An introduction to Progol.
[10]
Christer Samuelsson, Pasi Tapanainen, and Atro Voutilainen. 1996. Inducing Constraint Grammars. In Miclet Laurent and de la Higuera Colin, editors, Grammatical Inference: Learning Syntax from Sentences, pages 146--155. Springer Verlag.
[11]
Pasi Tapanainen. 1996. The Constraint Grammar Parser CG-2. Department of General Linguistics, University of Helsinki.

Cited By

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  • (2014)When Errors Become the RuleACM Computing Surveys10.1145/253418946:4(1-51)Online publication date: 1-Apr-2014
  • (2005)Inductive improvement of part-of-speech tagging and its effect on a terminology of molecular biologyProceedings of the 18th Canadian Society conference on Advances in Artificial Intelligence10.1007/11424918_38(366-376)Online publication date: 9-May-2005

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cover image DL Hosted proceedings
ACL '98/COLING '98: Proceedings of the 36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics - Volume 2
August 1998
768 pages

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  • Government of Canada
  • Université de Montréal

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Association for Computational Linguistics

United States

Publication History

Published: 10 August 1998

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Overall Acceptance Rate 85 of 443 submissions, 19%

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View all
  • (2014)When Errors Become the RuleACM Computing Surveys10.1145/253418946:4(1-51)Online publication date: 1-Apr-2014
  • (2005)Inductive improvement of part-of-speech tagging and its effect on a terminology of molecular biologyProceedings of the 18th Canadian Society conference on Advances in Artificial Intelligence10.1007/11424918_38(366-376)Online publication date: 9-May-2005

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