Skip to main content

Extensive Study on Automatic Verb Sense Disambiguation in Czech

  • Conference paper
  • 1035 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4188))

Abstract

In this paper we compare automatic methods for disambiguation of verb senses, in particular we investigate Naïve Bayes classifier, decision trees, and a rule-based method. Different types of features are proposed, including morphological, syntax-based, idiomatic, animacy, and WordNet-based features. We evaluate the methods together with individual feature types on two essentially different Czech corpora, VALEVAL and the Prague Dependency Treebank. The best performing methods and features are discussed.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Dang, H.T., Palmer, M.: The Role of Semantic Roles in Disambiguating Verb Senses. In: Proceedings of ACL, Ann Arbor MI (2005)

    Google Scholar 

  2. Ye, P.: Selectional Preferenced Based Verb Sense Disambiguation Using WordNet. In: Australasian Language Technology Workshop 2004, Australia, pp. 155–162 (2004)

    Google Scholar 

  3. Lopatková, M., Bojar, O., Semecký, J., Benešová, V., Žabokrtský, Z.: Valency lexicon of czech verbs VALLEX: Recent experiments with frame disambiguation. In: Matoušek, V., Mautner, P., Pavelka, T. (eds.) TSD 2005. LNCS, vol. 3658, pp. 99–106. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  4. Král, R.: Jaký to má význam? Ph.D. thesis, Masaryk University (2004)

    Google Scholar 

  5. Kocek, J., Kopřivová, M., Kučera, K. (eds.): Czech National Corpus - introduction and user handbook (in Czech), FF UK - ÚČNK, Prague (2000)

    Google Scholar 

  6. Bojar, O., Semecký, J., Benešová, V.: VALEVAL: Testing VALLEX Consistency and Experimenting with Word-Frame Disambiguation. Prague Bulletin of Mathematical Linguistics 83 (2005)

    Google Scholar 

  7. Charniak, E.: A Maximum-Entropy-Inspired Parser. In: Proceedings of NAACL 2000, Seattle, Washington, USA, pp. 132–139 (2000)

    Google Scholar 

  8. Hajič, J.: Building a Syntactically Annotated Corpus: The Prague Dependency Treebank. Issues of Valency and Meaning, pp. 106–132 (1998)

    Google Scholar 

  9. Sgall, P., Hajičová, E., Panevová, J.: The Meaning of the Sentence in its Semantic and Pragmatic Aspects, Academia, Prague. Czech Republic/Reidel Publishing Company, Dordrecht, Netherlands (1986)

    Google Scholar 

  10. McDonald, R., Pereira, F., Ribarov, K., Hajic, J.: Non-Projective Dependency Parsing using Spanning Tree Algorithms. In: Proceedings of HLT Conference and Conference on EMNLP, Vancouver, Canada, ACL, pp. 523–530 (2005)

    Google Scholar 

  11. Hajič, J.: Morphological Tagging: Data vs. Dictionaries. In: Proceedings of ANLP-NAACL Conference, Seattle, Washington, USA, pp. 94–101 (2000)

    Google Scholar 

  12. Fellbaum, C.: WordNet An Electronic Lexical Database. The MIT Press, Cambridge (1998)

    MATH  Google Scholar 

  13. Vossen, P., Bloksma, L., Rodriguez, H., Climent, S., Calzolari, N., Roventini, A., Bertagna, F., Alonge, A., Peters, W.: The EuroWordNet Base Concepts and Top Ontology. Technical report (1997)

    Google Scholar 

  14. Pala, K., Smrž, P.: Building Czech Wordnet. Romanian Journal of Information Science and Technology 7, 79–88 (2004)

    Google Scholar 

  15. Borgelt, C.: A Decision Tree Plug-In for DataEngine. In: Proceedings of 2nd Data Analysis Symposium, Aachen, Germany, MIT GmbH (1998)

    Google Scholar 

  16. Quinlan, J.R.: Data Mining Tools See5 and C5.0 (2005), http://www.rulequest.com/see5-info.html

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Semecký, J., Podveský, P. (2006). Extensive Study on Automatic Verb Sense Disambiguation in Czech. In: Sojka, P., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2006. Lecture Notes in Computer Science(), vol 4188. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11846406_30

Download citation

  • DOI: https://doi.org/10.1007/11846406_30

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-39090-9

  • Online ISBN: 978-3-540-39091-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics