[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
10.5555/1699571.1699596dlproceedingsArticle/Chapter ViewAbstractPublication PagesemnlpConference Proceedingsconference-collections
research-article
Free access

Improving verb clustering with automatically acquired selectional preferences

Published: 06 August 2009 Publication History

Abstract

In previous research in automatic verb classification, syntactic features have proved the most useful features, although manual classifications rely heavily on semantic features. We show, in contrast with previous work, that considerable additional improvement can be obtained by using semantic features in automatic classification: verb selectional preferences acquired from corpus data using a fully unsupervised method. We report these promising results using a new framework for verb clustering which incorporates a recent subcategorization acquisition system, rich syntactic-semantic feature sets, and a variation of spectral clustering which performs particularly well in high dimensional feature space.

References

[1]
Shane Bergsma, Dekang Lin, and Randy Goebel. Discriminative learning of selectional preference from unlabeled text. In Proc. of EMNLP, 2008.
[2]
Chris Brew and Sabine Schulte im Walde. Spectral clustering for german verbs. In Proc. of EMNLP, 2002.
[3]
Ted Briscoe, John Carroll, and Rebecca Watson. The second release of the rasp system. In Proc. of the COLING/ACL on Interactive presentation sessions, 2006.
[4]
Carsten Brockmann and Mirella Lapata. Evaluating and combining approaches to selectional preference acquisition. In Proc. of EACL, 2003.
[5]
Jinxiu Chen, Dong-Hong Ji, Chew Lim Tan, and Zheng-Yu Niu. Unsupervised relation disambiguation using spectral clustering. In Proc. of COLING/ACL, 2006.
[6]
Hoa Trang Dang. Investigations into the Role of Lexical Semantics in Word Sense Disambiguation. PhD thesis, CIS, University of Pennsylvania, 2004.
[7]
Katrin Erk. A simple, similarity-based model for selectional preferences. In Proc. of ACL, 2007.
[8]
David Graff. North american news text corpus. Linguistic Data Consortium, 1995.
[9]
Eric Joanis. Automatic Verb Classification Using a General Feature Space. Master's thesis, University of Toronto, 2002.
[10]
Eric Joanis, Suzanne Stevenson, and David James. A general feature space for automatic verb classification. Natural Language Engineering, 2008.
[11]
Karin Kipper-Schuler. VerbNet: A broad-coverage, comprehensive verb lexicon. 2005.
[12]
Anna Korhonen, Yuval Krymolowski, and Ted Briscoe. A large subcategorization lexicon for natural language processing applications. In Proc. of the 5th LREC, 2006.
[13]
Anna Korhonen, Yuval Krymolowski, and Nigel Collier. The Choice of Features for Classification of Verbs in Biomedical Texts. In Proc. of COLING, 2008.
[14]
Claudia Kunze and Lothar Lemnitzer. GermaNet-representation, visualization, application. In Proc. of LREC, 2002.
[15]
Lillian. Lee. On the effectiveness of the skew divergence for statistical language analysis. In Artificial Intelligence and Statistics, 2001.
[16]
Geoffrey Leech. 100 million words of english: the british national corpus. Language Research, 1992.
[17]
Beth. Levin. English verb classes and alternations: A preliminary investigation. Chicago, IL, 1993.
[18]
Jianguo Li and Chris Brew. Which Are the Best Features for Automatic Verb Classification. In Proc. of ACL, 2008.
[19]
Diana McCarthy. Lexical Acquisition at the Syntax-Semantics Interface: Diathesis Alternations, Sub-categorization Frames and Selectional Preferences. PhD thesis, University of Sussex, UK, 2001.
[20]
Marina. Meila. The multicut lemma. Technical report, University of Washington, 2001.
[21]
Marina Meila and Jianbo Shi. A random walks view of spectral segmentation. AISTATS, 2001.
[22]
George A. Miller. WordNet: a lexical database for English. Communications of the ACM, 1995.
[23]
Pedro J. Moreno, Purdy P. Ho, and Nuno Vasconcelos. A Kullback-Leibler divergence based kernel for SVM classification in multimedia applications. In Proc. of NIPS, 2004.
[24]
Andrew Y. Ng, Michael Jordan, and Yair Weiss. On spectral clustering: Analysis and an algorithm. In Proc. of NIPS, 2002.
[25]
Diarmuid Ó Séaghdha and Ann Copestake. Semantic classification with distributional kernels. In Proc. of COLING, 2008.
[26]
Judita Preiss, Ted Briscoe, and Anna Korhonen. A system for large-scale acquisition of verbal, nominal and adjectival subcategorization frames from corpora. In Proc. of ACL, 2007.
[27]
Jan Puzicha, Thomas Hofmann, and Joachim M. Buhmann. A theory of proximity based clustering: Structure detection by optimization. Pattern Recognition, 2000.
[28]
Sabine Schulte im Walde. Experiments on the automatic induction of german semantic verb classes. Computational Linguistics, 2006.
[29]
Sabine Schulte im Walde, Christian Hying, Christian Scheible, and Helmut Schmid. Combining EM Training and the MDL Principle for an Automatic Verb Classification incorporating Selectional Preferences. In Proc. of ACL, pages 496--504, 2008.
[30]
Lei Shi and Rada Mihalcea. Putting pieces together: Combining FrameNet, VerbNet and WordNet for robust semantic parsing. In Proc. of CICLING, 2005.
[31]
Suzanne Stevenson and Eric Joanis. Semi-supervised verb class discovery using noisy features. In Proc. of HLT-NAACL 2003, pages 71--78, 2003.
[32]
Lin Sun, Anna Korhonen, and Yuval Krymolowski. Verb class discovery from rich syntactic data. Lecture Notes in Computer Science, 4919:16, 2008.
[33]
Robert Swier and Suzanne Stevenson. Unsupervised semantic role labelling. In Proc. of EMNLP, 2004.
[34]
Deepak Verma and Marina Meila. Comparison of spectral clustering methods. Advances in Neural Information Processing Systems (NIPS 15), 2003.
[35]
Andreas Vlachos, Anna Korhonen, and Zoubin Ghahramani. Unsupervised and constrained dirichlet process mixture models for verb clustering. In Proc. of the Workshop on Geometrical Models of Natural Language Semantics, 2009.
[36]
Ulrike von Luxburg. A tutorial on spectral clustering. Statistics and Computing, 2007.
[37]
Beñat Zapirain, Eneko Agirre, and Lluís Màrquez. Robustness and generalization of role sets: PropBank vs. VerbNet. In Proc. of ACL, 2008.

Cited By

View all
  • (2015)Finding the Differences between the Perceptions of Experts and the Public in the Field of DiabetesProceedings of the 24th International Conference on World Wide Web10.1145/2740908.2742773(57-58)Online publication date: 18-May-2015
  • (2015)Identifying synonymy between relational phrases using word embeddingsJournal of Biomedical Informatics10.1016/j.jbi.2015.05.01056:C(94-102)Online publication date: 1-Aug-2015
  • (2014)Verb Clustering for Brazilian PortugueseProceedings of the 15th International Conference on Computational Linguistics and Intelligent Text Processing - Volume 840310.1007/978-3-642-54906-9_3(25-39)Online publication date: 6-Apr-2014
  • Show More Cited By

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image DL Hosted proceedings
EMNLP '09: Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
August 2009
616 pages
ISBN:9781932432626

Publisher

Association for Computational Linguistics

United States

Publication History

Published: 06 August 2009

Qualifiers

  • Research-article

Acceptance Rates

Overall Acceptance Rate 73 of 234 submissions, 31%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)21
  • Downloads (Last 6 weeks)2
Reflects downloads up to 09 Jan 2025

Other Metrics

Citations

Cited By

View all
  • (2015)Finding the Differences between the Perceptions of Experts and the Public in the Field of DiabetesProceedings of the 24th International Conference on World Wide Web10.1145/2740908.2742773(57-58)Online publication date: 18-May-2015
  • (2015)Identifying synonymy between relational phrases using word embeddingsJournal of Biomedical Informatics10.1016/j.jbi.2015.05.01056:C(94-102)Online publication date: 1-Aug-2015
  • (2014)Verb Clustering for Brazilian PortugueseProceedings of the 15th International Conference on Computational Linguistics and Intelligent Text Processing - Volume 840310.1007/978-3-642-54906-9_3(25-39)Online publication date: 6-Apr-2014
  • (2013)A computational model of logical metonymyACM Transactions on Speech and Language Processing 10.1145/2483969.248397310:3(1-28)Online publication date: 11-Jul-2013
  • (2013)Evaluating the premises and results of four metaphor identification systemsProceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I10.1007/978-3-642-37247-6_38(471-486)Online publication date: 24-Mar-2013
  • (2012)Learning syntactic verb frames using graphical modelsProceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 110.5555/2390524.2390583(420-429)Online publication date: 8-Jul-2012
  • (2011)Hierarchical verb clustering using graph factorizationProceedings of the Conference on Empirical Methods in Natural Language Processing10.5555/2145432.2145543(1023-1033)Online publication date: 27-Jul-2011
  • (2011)A weakly-supervised approach to argumentative zoning of scientific documentsProceedings of the Conference on Empirical Methods in Natural Language Processing10.5555/2145432.2145464(273-283)Online publication date: 27-Jul-2011
  • (2010)Investigating the cross-linguistic potential of VerbNetProceedings of the 23rd International Conference on Computational Linguistics10.5555/1873781.1873900(1056-1064)Online publication date: 23-Aug-2010
  • (2010)Identifying the information structure of scientific abstractsProceedings of the 2010 Workshop on Biomedical Natural Language Processing10.5555/1869961.1869974(99-107)Online publication date: 15-Jul-2010
  • Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Login options

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media