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A rule-based approach to prepositional phrase attachment disambiguation

Published: 05 August 1994 Publication History

Abstract

In this paper, we describe a new corpus-based approach to prepositional phrase attachment disambiguation, and present results comparing performance of this algorithm with other corpus-based approaches to this problem.

References

[1]
{AS88} G. Altmann and M. Steedman. Interaction with context during human sentence processing. Cognition, 30:191--238, 1988.
[2]
{BDd + 92} Peter F. Brown, Vincent J. Della Pietra, Peter V. deSouza, Jennifer C. Lai, and Robert L. Mercer. Class-based n-gram models of natural language. Computational Linguistics, 18(4):467--480, December 1992.
[3]
{BPV91} R. Basili, M. Pazienza, and P. Velardi. Combining NLP and statistical techniques for lexical acquisition. In Proceedings of the AAAI Fall Symposium on Probabilistic Approaches to Natural Language, Cambridge, Massachusetts, October 1991.
[4]
{Bri92} E. Brill. A simple rule-based part of speech tagger. In Proceeding of the Third Conference on Applied Natural Language Processing, ACL, Trento, Italy, 1992.
[5]
{Bri93a} E. Brill. Automatic grammar induction and parsing free text: A transformation-based approach. In Proceedings of the 31st Meeting of the Association of Computational Linguistics, Columbus, Oh., 1993.
[6]
{Bri93b} E. Brill. A Corpus-Based Approach to Language Learning. PhD thesis, Department of Computer and Information Science, University of Pennsylvania, 1993.
[7]
{Bri94} E. Brill. Some advances in rule-based part of speech tagging. In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), Seattle, Wa., 1994.
[8]
{Fra78} L. Frazier. On comprehending sentences: syntactic parsing strategies. PhD thesis, University of Connecticut, 1978.
[9]
{HR91} D. Hindle and M. Rooth. Structural ambignity and lexical relations. In Proceedings of the 29th Annual Meeting of the Association for Computational Linguistics, Berkeley, Ca., 1991.
[10]
{HR93} D. Hindle and M. Rooth. Structural ambiguity and lexical relations. Computational Linguistics, 19(1):103--120, 1993.
[11]
{Kim73} J. Kimball. Seven principles of surface structure parsing in natural language. Cognition, 2, 1973.
[12]
{Mil90} G. Miller. Wordnet: an on-line lexical database. International Journal of Lexicography, 3(4), 1990.
[13]
{MSM93} M. Marcus, B. Santorini, and M. Marcinkiewicz. Building a large annotated corpus of English: the Penn Treebank. Computational Linguistics, 19(2), 1993.
[14]
{Res93a} P. Resnik. Selection and Information: A Class-Based Approach to Lexical Relationships. PhD thesis, University of Pennsylvania, December 1993. (Institute for Research in Cognitive Science report IRCS-93-42).
[15]
{Res93b} P. Resnik. Semantic classes and syntactic ambiguity. In Proceedings of the ARPA Workshop on Human Language Technology. Morgan Kaufman, 1993.
[16]
{Res93c} P. Resnik. Semantic classes and syntactic ambiguity. ARPA Workshop on Human Language Technology, March 1993. Princeton.
[17]
{RH93} P. Resnik and M. Hearst. Syntactic ambiguity and conceptual relations. In K. Church, editor, Proceedings of the ACL Workshop on Very Large Corpora, pages 58--64, June 1993.
[18]
{RM94} L. Ramshaw and M. Marcus. Exploring the statistical derivation of transformational rule sequences for part-of-speech tagging. In J. Klavans and P. Resnik, editors, The Balancing Act: Proceedings of the ACL Workshop on Combining Symbolic and Statistical Approaches to Language, New Mexico State University, July 1994.
[19]
{RR94} A. Ratnaparkhi and S. Roukos. A maximum entropy model for prepositional phrase attachment. In Proceedings of the ARPA Workshop on Human Language Technology, Plainsboro, NJ, March 1994.
[20]
{WAB + 91} R. Weischedel, D. Ayuso, R. Bobrow, S. Boisen, R. Ingria, and J. Palmucci. Partial parsing: a report of work in progress. In Proceedings of the Fourth DARPA Speech and Natural Language Workshop, February 1991, 1991.
[21]
{WFB90} G. Whittemore, K. Ferrara, and H. Brunner. Empirical study of predictive powers of simple attachment schemes for post-modifier prepositional phrases. In Proceedings of the 28th Annual Meeting of the Association for Computational Linguistics, 1990.

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  1. A rule-based approach to prepositional phrase attachment disambiguation

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      Published In

      cover image DL Hosted proceedings
      COLING '94: Proceedings of the 15th conference on Computational linguistics - Volume 2
      August 1994
      661 pages

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      Association for Computational Linguistics

      United States

      Publication History

      Published: 05 August 1994

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      • (2014)When Errors Become the RuleACM Computing Surveys10.1145/253418946:4(1-51)Online publication date: 1-Apr-2014
      • (2012)Transforming trees to improve syntactic convergenceProceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning10.5555/2390948.2391041(863-872)Online publication date: 12-Jul-2012
      • (2011)Simple semi-supervised learning for prepositional phrase attachmentProceedings of the 12th International Conference on Parsing Technologies10.5555/2206329.2206345(129-139)Online publication date: 5-Oct-2011
      • (2010)A methodology for automatic identification of nocuous ambiguityProceedings of the 23rd International Conference on Computational Linguistics10.5555/1873781.1873918(1218-1226)Online publication date: 23-Aug-2010
      • (2010)Automatic detection of nocuous coordination ambiguities in natural language requirementsProceedings of the 25th IEEE/ACM International Conference on Automated Software Engineering10.1145/1858996.1859007(53-62)Online publication date: 20-Sep-2010
      • (2007)Weakly-supervised discovery of named entities using web search queriesProceedings of the sixteenth ACM conference on Conference on information and knowledge management10.1145/1321440.1321536(683-690)Online publication date: 6-Nov-2007
      • (2006)Postnominal prepositional phrase attachment in proteomicsProceedings of the HLT-NAACL BioNLP Workshop on Linking Natural Language and Biology10.5555/1654415.1654432(82-89)Online publication date: 8-Jun-2006
      • (2006)Postnominal prepositional phrase attachment in proteomicsProceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis10.5555/1567619.1567636(82-89)Online publication date: 8-Jun-2006
      • (2006)The benefit of stochastic PP attachment to a rule-based parserProceedings of the COLING/ACL on Main conference poster sessions10.5555/1273073.1273102(223-230)Online publication date: 17-Jul-2006
      • (2006)Prosodic words prediction from lexicon words with CRF and TBL joint methodProceedings of the 5th international conference on Chinese Spoken Language Processing10.1007/11939993_20(161-168)Online publication date: 13-Dec-2006
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