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An Approach to Automatic Construction of Lexical Relations Between Chinese Nouns from Machine Readable Dictionary

  • Yi Hu
  • Ruzhan Lu
  • Xuening Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3513)

Abstract

In this paper, a machine readable dictionary is utilized to acquire Chinese noun pairs satisfying five lexical relations. For low accuracy of current Chinese parser, our method is different from the traditional ones that use parsing firstly. The new method is designed to be a three-step procedure. Firstly, it annotates the paraphrase of some nominal entries that are used as training data. Secondly, patterns that denote lexical relations between nouns are defined and the applicability of the patterns is learnt from training Maximum Entropy model. At last, these patterns are applied to the remaining portion of the dictionary. A relatively satisfying result is achieved.

Keywords

Maximum Entropy Contextual Feature Lexical Knowledge Automatic Construction Noun Pair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Miller, G.A., Beckwith, R., et al.: Introduction to wordnet: An on-line lexical database. Journal of Lexicography 3(4), 235–244 (1990)CrossRefGoogle Scholar
  2. 2.
    Zhendong, D.: HowNet, http://www.keenage.com/
  3. 3.
    Jensen, K., Binot, J.L.: Disambiguating prepositional phrase attachments by using on-line dictionary definitions. Computational Linguistics 13(3-4), 251–260 (1987)Google Scholar
  4. 4.
    Della Pietra, S., Della Pietra, V., Lafferty, J.: Inducing features of random fields. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(4), 380–393 (1997)CrossRefGoogle Scholar
  5. 5.
    Ruzhan, L., Guangjin, J.: The new angle of view to modern Chinese research. In: The third national workshop on language and literal application (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Yi Hu
    • 1
  • Ruzhan Lu
    • 1
  • Xuening Li
    • 1
  1. 1.Department of Computer Science and EngineeringShanghai Jiaotong UniversityShanghaiChina

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