Skip to main content

Syntactic Parsing with Hierarchical Modeling

  • Conference paper
Information Retrieval Technology (AIRS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4993))

Included in the following conference series:

Abstract

This paper proposes a hierarchical model to parse both English and Chinese sentences. This is done by iteratively constructing simple constituents first, so that complex ones could be detected reliably with richer contextual information in the following processes. Evaluation on the Penn WSJ Treebank and the Penn Chinese Treebank using maximum entropy models shows that our method can achieve a good performance with more flexibility for future improvement.

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

Access this chapter

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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bikel, D.M., Chiang, D.: Two statistical parsing models applied to the Chinese Treebank. In: Proceedings of 2nd Chinese Language Processing Workshop (2000)

    Google Scholar 

  2. Charniak, E.: Statistical parsing with a context-free grammar and word statistics. In: Proceedings of AAAI 1997 (1997)

    Google Scholar 

  3. Chiang, D., Bikel, D.M.: Recovering latent information in treebanks. In: Proceedings of COLING 2002, pp. 183–189 (2002)

    Google Scholar 

  4. Collins, M.: 1999. Head-driven statistical model for natural language parsing [D]. Ph. D. Thesis, the University of Pennsylvania (1999)

    Google Scholar 

  5. Levy, R., Manning, C.: Is it harder to parse Chinese, or the Chinese Treebank? In: Dignum, F.P.M. (ed.) ACL 2003. LNCS (LNAI), vol. 2922, Springer, Heidelberg (2004)

    Google Scholar 

  6. Magerman, D.M.: Statistical decision-tree models for parsing. In: Proceedings of the 33rd Annual Meeting of the Association for Computational Linguistics (1995)

    Google Scholar 

  7. Ratnaparkhi, A.: Learning to parse natural language with maximum entropy models. Machine Learning 341(2/3), 151–176 (1999)

    Article  Google Scholar 

  8. Xiong, D., Li, S.L., Liu, Q., et al.: Parsing the Penn Chinese treebank with semantic knowledge. In: Proceedings of the 2nd IJCNLP, pp. 70–81 (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Hang Li Ting Liu Wei-Ying Ma Tetsuya Sakai Kam-Fai Wong Guodong Zhou

Rights and permissions

Reprints and permissions

Copyright information

© 2008 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Li, J., Zhou, G., Zhu, Q., Qian, P. (2008). Syntactic Parsing with Hierarchical Modeling. In: Li, H., Liu, T., Ma, WY., Sakai, T., Wong, KF., Zhou, G. (eds) Information Retrieval Technology. AIRS 2008. Lecture Notes in Computer Science, vol 4993. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68636-1_64

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-68636-1_64

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68633-0

  • Online ISBN: 978-3-540-68636-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics