Parsing Without Grammar Rules

  • Yuji Matsumoto
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4201)


In this article, we present and contrast recent statistical approaches to word dependency parsing and lexicalized formalisms for grammar and semantics. We then consider the possibility of integrating those two extreme ideas, which leads to fully lexicalized parsing without any syntactic grammar rules.


dependency parsing lexicalized grammar lexical semantics 


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  1. 1.
    Charniak, E.: A Maximum-Entropy-Inspired Parser. In: 1st Meeting of the North American Chapter of the Association for Computational Linguistics, pp. 132–139 (2000)Google Scholar
  2. 2.
    Cheng, Y., Asahara, M., Matsumoto, Y.: Deterministic Dependency Structure Analyzer for Chinese. In: Su, K.-Y., Tsujii, J., Lee, J.-H., Kwong, O.Y. (eds.) IJCNLP 2004. LNCS (LNAI), vol. 3248, pp. 500–508. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  3. 3.
    Collins, M.: Three Generative, Lexicalised Models for Statistical Parsing. In: 35th Annual Meeting of the Association for Computational Linguistics and 8th Conference of the European Chapter of the Association for Computational Linguistics, pp. 16–23 (1997)Google Scholar
  4. 4.
    Davis, A.R. (ed.): Linking by Types in the Heirarchical Lexicon. CSLI Publications, Stanford (2001)Google Scholar
  5. 5.
    Goldberg, A.E.: Constructions: A Construction Grammar Approach to Argument Structure. The University Chicago Press, Chicago (1995)Google Scholar
  6. 6.
    Jackendoff, R.: Semantic Structures, Current Studies in Linguistics 18. The MIT Press, Cambridge (1990)Google Scholar
  7. 7.
    Kudo, T., Matsumoto, Y.: Japanese Dependency Analysis using Cascaded Chunking. In: 6th Conference on Natural Language Learning, pp. 63–69 (2002)Google Scholar
  8. 8.
    Marcus, M.P., Santorini, B., Marcinkiewicz, M.A.: Building a Large Annotated Corpus of English:The Penn Treebank. Computational Linguistics 19(2), 313–330 (1993)Google Scholar
  9. 9.
    McDonald, R., Crammer, K., Pereira, F.: Online Large-Margin Training of Dependency Parsers. In: 43rd Annual Meeting of the Association for Computational Linguistics: Proceedings of the Conference, pp. 91–98 (2005)Google Scholar
  10. 10.
    McDonald, R., Pereira, F., Hajic, J.: Non-Projective Dependency Parsing using Spanning Tree Algorithms. HLT-EMNLP (2005)Google Scholar
  11. 11.
    Nivre, J., Scholz, M.: Deterministic Dependency Parsing of English Text. In: 20th International Conference on Computational Linguistics, pp. 64–70 (2004)Google Scholar
  12. 12.
    Östman, J.-O., Fried, M.: Construction Grammars: Cognitive Grounding and Theoretical Extensions. John Benjamins Publishing Company, Amsterdam (2005)Google Scholar
  13. 13.
    Pustejovsky, J.: The Generative Lexicon. The MIT Press, Cambridge (1995)Google Scholar
  14. 14.
    Rambow, O. (ed.): Tree Adjoining Grammars: Formalisms, Linguistic Analysis and Processing. CSLI Lecture Notes, vol. 107. CSLI Publications, Stanford (2000)zbMATHGoogle Scholar
  15. 15.
    Sag, I.A., Wasow, T., Bender, E.M. (eds.): Syntactic Theory: A Formal Introduction. CSLI Lecture Notes, vol. 152. CSLI Publications, Stanford (2003)Google Scholar
  16. 16.
    Yamada, H., Matsumoto, Y.: Statistical Dependency Analysis with Support Vector Machines. In: 8th International Workshop on Parsing Technologies, pp. 195–206 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yuji Matsumoto
    • 1
  1. 1.Graduate School of Information ScienceNara Institute of Science and TechnologyNaraJapan

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