Abstract
We address the problem of classifying multiword expression tokens in running text. We focus our study on Verb-Noun Constructions (VNC) that vary in their idiomaticity depending on context. VNC tokens are classified as either idiomatic or literal. Our approach hinges upon the assumption that a literal VNC will have more in common with its component words than an idiomatic one. Commonality is measured by contextual overlap. To this end, we set out to explore different contextual variations and different similarity measures. We also identify a new data set OPAQUE that comprises only non-decomposable VNC expressions. Our approach yields state of the art performance with an overall accuracy of 77.56% on a TEST data set and 81.66% on the newly characterized data set OPAQUE.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Sag, I.A., Baldwin, T., Bond, F., Copestake, A.A., Flickinger, D.: Multiword expressions: A pain in the neck for NLP. In: Gelbukh, A. (ed.) CICLing 2002. LNCS, vol. 2276, pp. 1–15. Springer, Heidelberg (2002)
Villavicencio, A., Copestake, A.: On the nature of idioms. In: LinGO Working Paper No. 2002-2004 (2002)
Melamed, D.I.: Automatic discovery of non-compositional compounds in parallel data. In: Proceedings of the 2nd Conference on Empirical Methods in Natural Language Processing (EMNLP 1997), Providence, RI, USA, pp. 97–108 (1997)
Lin, D.: Automatic identification of noncompositional phrases. In: Proceedings of ACL 1999, Univeristy of Maryland, College Park, Maryland, USA, pp. 317–324 (1999)
Baldwin, T., Bannard, C., Tanaka, T., Widdows, D.: An empirical model of multiword expression decomposability. In: Proceedings of the ACL 2003 Workshop on Multiword Expressions, Morristown, NJ, USA, pp. 89–96 (2003)
na Villada Moirón, B., Tiedemann, J.: Identifying idiomatic expressions using automatic word-alignment. In: Proceedings of the EACL 2006 Workshop on Multiword Expressions in a Multilingual Context, Morristown, NJ, USA, pp. 33–40 (2006)
Fazly, A., Stevenson, S.: Distinguishing subtypes of multiword expressions using linguistically-motivated statistical measures. In: Proceedings of the Workshop on A Broader Perspective on Multiword Expressions, Prague, Czech Republic, Association for Computational Linguistics, pp. 9–16 (2007)
Van de Cruys, T., Villada Moirón, B.n.: Semantics-based multiword expression extraction. In: Proceedings of the Workshop on A Broader Perspective on Multiword Expressions, Prague, Czech Republic, Association for Computational Linguistics, pp. 25–32 (2007)
Cook, P., Fazly, A., Stevenson, S.: The VNC-Tokens Dataset. In: Proceedings of the LREC Workshop on Towards a Shared Task for Multiword Expressions (MWE 2008), Marrakech, Morocco (2008)
Cook, P., Fazly, A., Stevenson, S.: Pulling their weight: Exploiting syntactic forms for the automatic identification of idiomatic expressions in context. In: Proceedings of the Workshop on A Broader Perspective on Multiword Expressions, Prague, Czech Republic, Association for Computational Linguistics, pp. 41–48 (2007)
Resnik, P.: Selectional preference and sense disambiguation. In: Proceedings of the ACL SIGLEX Workshop on Tagging Text with Lexical Semantics: Why, What, and How?, Washington, DC, USA (1997)
Katz, G., Giesbrecht, E.: Automatic identification of non-compositional multi-word expressions using latent semantic analysis. In: Proceedings of the Workshop on Multiword Expressions: Identifying and Exploiting Underlying Properties, Sydney, Australia, Association for Computational Linguistics, pp. 12–19 (2006)
Schone, P., Juraksfy, D.: Is knowledge-free induction of multiword unit dictionary headwords a solved problem? In: Proceedings of Empirical Methods in Natural Language Processing, Pittsburg, PA, USA, pp. 100–108 (2001)
Mitchell, J., Lapata, M.: Vector-based models of semantic composition. In: Proceedings of ACL 2008: HLT, Columbus, Ohio, Association for Computational Linguistics, pp. 236–244 (2008)
Manning, C.D., Schütze, H.: Foundations of Statistical Natural Language Processing. MIT Press, Cambridge (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Diab, M.T., Krishna, M. (2009). Unsupervised Classification of Verb Noun Multi-Word Expression Tokens. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2009. Lecture Notes in Computer Science, vol 5449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00382-0_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-00382-0_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00381-3
Online ISBN: 978-3-642-00382-0
eBook Packages: Computer ScienceComputer Science (R0)