Article

Free access

A new statistical parser based on bigram lexical dependencies

Author:

Michael John CollinsAuthors Info & Claims

ACL '96: Proceedings of the 34th annual meeting on Association for Computational Linguistics

Pages 184 - 191

https://doi.org/10.3115/981863.981888

Published: 24 June 1996 Publication History

Abstract

This paper describes a new statistical parser which is based on probabilities of dependencies between head-words in the parse tree. Standard bigram probability estimation techniques are extended to calculate probabilities of dependencies between pairs of words. Tests using Wall Street Journal data show that the method performs at least as well as SPATTER (Magerman 95; Jelinek et al. 94), which has the best published results for a statistical parser on this task. The simplicity of the approach means the model trains on 40,000 sentences in under 15 minutes. With a beam search strategy parsing speed can be improved to over 200 sentences a minute with negligible loss in accuracy.

References

[1]

E. Black et al. 1991. A Procedure for Quantitatively Comparing the Syntactic Coverage of English Grammars. Proceedings of the February 1991 DARPA Speech and Natural Language Workshop.

Digital Library

[2]

T. Briscoe and J. Carroll. 1993. Generalized LR Parsing of Natural Language (Corpora) with Unification-Based Grammars. Computational Linguistics, 19(1):25--60.

Digital Library

[3]

K. Church. 1988. A Stochastic Parts Program and Noun Phrase Parser for Unrestricted Text. Second Conference on Applied Natural Language Processing, ACL.

Digital Library

[4]

M. Collins and J. Brooks. 1995. Prepositional Phrase Attachment through a Backed-off Model. Proceedings of the Third Workshop on Very Large Corpora, pages 27--38.

[5]

D. Hindle and M. Rooth. 1993. Structural Ambiguity and Lexical Relations. Computational Linguistics, 19(1):103--120.

Digital Library

[6]

F. Jelinek. 1990. Self-organized Language Modeling for Speech Recognition. In Readings in Speech Recognition. Edited by Waibel and Lee. Morgan Kaufmann Publishers.

Digital Library

[7]

F. Jelinek, J. Lafferty, D. Magerman, R. Mercer, A. Ratnaparkhi, S. Roukos. 1994. Decision Tree Parsing using a Hidden Derivation Model. Proceedings of the 1994 Human Language Technology Workshop, pages 272--277.

Digital Library

[8]

J. Lafferty, D. Sleator and, D. Temperley. 1992. Grammatical Trigrams: A Probabilistic Model of Link Grammar. Proceedings of the 1992 AAAI Fall Symposium on Probabilistic Approaches to Natural Language.

[9]

D. Magerman. 1995. Statistical Decision-Tree Models for Parsing. Proceedings of the 33rd Annual Meeting of the Association for Computational Linguistics, pages 276--283.

Digital Library

[10]

D. Magerman and M. Marcus. 1991. Pearl: A Probabilistic Chart Parser. Proceedings of the 1991 European ACL Conference, Berlin, Germany.

Digital Library

[11]

M. Marcus, B. Santorini and M. Marcinkiewicz. 1993. Building a Large Annotated Corpus of English: the Penn Treebank. Computational Linguistics, 19(2):313--330.

Digital Library

[12]

F. Pereira and Y. Schabes. 1992. Inside-Outside Reestimation from Partially Bracketed Corpora. Proceedings of the 30th Annual Meeting of the Association for Computational Linguistics, pages 128--135.

Digital Library

[13]

L. Ramshaw and M. Marcus. 1995. Text Chunking using Transformation-Based Learning. Proceedings of the Third Workshop on Very Large Corpora, pages 82--94.

[14]

A. Ratnaparkhi. 1996. A Maximum Entropy Model for Part-Of-Speech Tagging. Conference on Empirical Methods in Natural Language Processing, May 1996.

[15]

M. M. Wood. 1993. Categorial Grammars, Routledge.

Cited By

Gildea DSatta GPeng X(2019)Ordered tree decomposition for hrg rule extractionComputational Linguistics10.1162/coli_a_0035045:2(339-379)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1162/coli_a_00350
Hung CChen S(2016)Word sense disambiguation based sentiment lexicons for sentiment classificationKnowledge-Based Systems10.1016/j.knosys.2016.07.030110:C(224-232)Online publication date: 15-Oct-2016
https://dl.acm.org/doi/10.1016/j.knosys.2016.07.030
Aggarwal CZhao P(2013)Towards graphical models for text processingKnowledge and Information Systems10.1007/s10115-012-0552-336:1(1-21)Online publication date: 1-Jul-2013
https://dl.acm.org/doi/10.1007/s10115-012-0552-3
Show More Cited By

A new statistical parser based on bigram lexical dependencies

Recommendations

Combining machine-readable lexical resources with a principle-based parser
A Noun-Predicate Bigram-Based Similarity Measure for Lexical Relations
GoTAL '08: Proceedings of the 6th international conference on Advances in Natural Language Processing

The method outlined in this paper demonstrates that the information-theoretic similarity measure and noun-predicate bigrams are effective methods for creating lists of semantically-related words for lexical database work. Our experiments revealed that ...
Supertagging for a Statistical HPSG Parser for Spanish
SLSP 2015: Proceedings of the Third International Conference on Statistical Language and Speech Processing - Volume 9449

We created a supertagger for the Spanish language aimed at disambiguating the HPSG lexical frames for the verbs in a sentence. The supertagger uses a CRF model and achieves an accuracy of 83.58ï ź% for the verb classes on the test set. The tagset ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image DL Hosted proceedings

ACL '96: Proceedings of the 34th annual meeting on Association for Computational Linguistics

June 1996

399 pages

Program Chairs:
Aravind Joshi
University of Pennsylvania, Philadelphia, PA
,
Martha Palmer
University of Pennsylvania, Philadelphia, PA

Publisher

Association for Computational Linguistics

United States

Publication History

Published: 24 June 1996

Qualifiers

Article

Acceptance Rates

Overall Acceptance Rate 85 of 443 submissions, 19%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

129
Total Citations
View Citations
1,533
Total Downloads

Downloads (Last 12 months)31
Downloads (Last 6 weeks)7

Reflects downloads up to 26 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

Gildea DSatta GPeng X(2019)Ordered tree decomposition for hrg rule extractionComputational Linguistics10.1162/coli_a_0035045:2(339-379)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1162/coli_a_00350
Hung CChen S(2016)Word sense disambiguation based sentiment lexicons for sentiment classificationKnowledge-Based Systems10.1016/j.knosys.2016.07.030110:C(224-232)Online publication date: 15-Oct-2016
https://dl.acm.org/doi/10.1016/j.knosys.2016.07.030
Aggarwal CZhao P(2013)Towards graphical models for text processingKnowledge and Information Systems10.1007/s10115-012-0552-336:1(1-21)Online publication date: 1-Jul-2013
https://dl.acm.org/doi/10.1007/s10115-012-0552-3
Germann U(2012)Syntax-aware phrase-based statistical machine translationProceedings of the Seventh Workshop on Statistical Machine Translation10.5555/2393015.2393055(292-297)Online publication date: 7-Jun-2012
https://dl.acm.org/doi/10.5555/2393015.2393055
Radev DAbu-Jbara A(2012)Rediscovering ACL discoveries through the lens of ACL anthology network citing sentencesProceedings of the ACL-2012 Special Workshop on Rediscovering 50 Years of Discoveries10.5555/2390507.2390509(1-12)Online publication date: 10-Jul-2012
https://dl.acm.org/doi/10.5555/2390507.2390509
Stenetorp PTopić GPyysalo SOhta TKim JTsujii JTsujii JKim JPyysalo S(2011)BioNLP Shared Task 2011Proceedings of the BioNLP Shared Task 2011 Workshop10.5555/2107691.2107707(112-120)Online publication date: 24-Jun-2011
https://dl.acm.org/doi/10.5555/2107691.2107707
Agirre EBengoetxea KGojenola KNivre JLin D(2011)Improving dependency parsing with semantic classesProceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 210.5555/2002736.2002871(699-703)Online publication date: 19-Jun-2011
https://dl.acm.org/doi/10.5555/2002736.2002871
Kuhlmann MGómez-Rodríguez CSatta GLin D(2011)Dynamic programming algorithms for transition-based dependency parsersProceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 110.5555/2002472.2002558(673-682)Online publication date: 19-Jun-2011
https://dl.acm.org/doi/10.5555/2002472.2002558
Xu HAbdelRahman SLu YDenny JDoan S(2011)Applying semantic-based probabilistic context-free grammar to medical language processing - A preliminary study on parsing medication sentencesJournal of Biomedical Informatics10.1016/j.jbi.2011.08.00944:6(1068-1075)Online publication date: 1-Dec-2011
https://dl.acm.org/doi/10.1016/j.jbi.2011.08.009
Liu SLi SZhao TZhang MLiu PJoshi AHuang CJurafsky D(2010)Head-modifier relation based non-lexical reordering model for phrase-based translationProceedings of the 23rd International Conference on Computational Linguistics: Posters10.5555/1944566.1944652(748-756)Online publication date: 23-Aug-2010
https://dl.acm.org/doi/10.5555/1944566.1944652
Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents