Skip to main content

Evaluation of Feature Combination for Effective Structural Disambiguation

  • Conference paper
  • 947 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2945))

Abstract

In this paper, we present the useful features of a syntactic constituent for a probabilistic parsing model and analyze the combination of the features in order to disambiguate parse trees effectively. Unlike most of previous works focusing on the features of a single head, the features of a functional head, the features of a content head, and the features of size are utilized in this study. Experimental results show that the combination of different features such as the functional head feature and the size feature is prefered to the combination of similar features such as the functional head feature and the content head feature. Besides, it is remarkable that the function feature is more useful than the combination of the content feature and the size feature.

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. Collins, M.: Head-Driven Statistical Models for Natural Language Parsing. Ph.D. Thesis, University of Pennsylvania (1999)

    Google Scholar 

  2. Magerman, D.M.: Statistical Decision-Tree Models for Parsing. In: Proceedings of ACL 1995, pp. 276–283 (1995)

    Google Scholar 

  3. Lee, K.-J., Kim, J.-H., Kim, K.-C.: Syntactic Analysis of Korean Sentences based on Restricted Phrase Structure Grammar. Journal of the Korea Information Science Society 25(4), 722–732 (1998) (written in Korean)

    Google Scholar 

  4. Charniak, E.: Immediate-Head Parsing for Language Models. In: Proceedings of ACL 2001, pp. 116–123 (2001)

    Google Scholar 

  5. Kwak, Y.-J., Hwang, Y.-S., Chung, H.-J., Park, S.-Y., Lee, S.-Z., Rim, H.-C.: GLR Parser with Conditional Action Model(CAM). In: Proceedings of NLPRS 2001, pp. 359–366 (2001)

    Google Scholar 

  6. Black, E., Jelinek, F., Lafferty, J., Magerman, D.M., Mercer, R., Roukos, S.: Towards History-based Grammars: Using Richer Models for Probabilistic Parsing. In: Proceedings of In Proceedings of ACL 1993, pp. 31–37 (1993)

    Google Scholar 

  7. Goodman, J.: Parsing Algorithms and Metrics. In: Proceedings of ACL 1996, pp. 177–183 (1996)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Park, SY., Kwak, YJ., Lim, JH., Rim, HC. (2004). Evaluation of Feature Combination for Effective Structural Disambiguation. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2004. Lecture Notes in Computer Science, vol 2945. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24630-5_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-24630-5_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21006-1

  • Online ISBN: 978-3-540-24630-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics