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    Abstract:

    This paper proposes an algorithm of automaticallytagging the POS(part of speech) of Chinese words which is based on integration of the statistical technique and the rule technique with the priority of the quantitative statistical analysis. The confidence intervals in the estimation of parameters is employed in the algorithm, and this makes the high-accuracy quantitative statistical technique as the top priority of tagging a corpus. Then the untagging part of the corpus is tagged in terms of rules, and some errors by statistics can be corrected by rules. Both closed and opened tests indicated that the accuracies of the algorithm are 98.9% and 98.1% respectively without consideration of both unknown words and segmentation errors.

    Reference
    1  Brill E, Magerman D, Marcus M et al. Deducing linguistic structure from the statistics of large corpus. In: Proceedings of the DARPA Speech and Natural Language Workshop. Hidden Valley PA: Addison Wesley Longman Limited, USA, 1990. 275~282 2  Zhao Tie-jun, Mao Cheng-jiang, Zhang Min et al. Solving the ambiguity of Chinese POS in the CEMT-III system. Chinese Information Journal, 1994,7(4):52~59 3  Bernard Merialdo. Tagging English text with a probailistic model. Computational Linguistics, 1994,20(2):1~29 4  Zhang Chi. Research on the algorithm of POS tagging on Chinese corpus based on statistics [Bachelor Thesis]. Harbin Institute of Technology, 1996 5  Bai Shuan-hu. Research on the algorithm of POS tagging on Chinese corpus based on statistics [Master Thesis]. Tsinghua University, 1992 6  Zhou Qiang. An algorithm of tagging Chinese POS based on statistics and rule. Chinese Information Journal, 1996,9(3):1~9 7  Elliott Macklovith. Where the tagger falters. In: Proceedings of TMI-92, the 4th International Conference on Theoretical and Methodological Issues in Machine Translation. Pierre Isabelle, Bell Canada Publishing House, Canada, 1992. 113~126 8  Ido Dagan, Alon Itai. Word sense disambiguation using a second language monolingual corpus. Computational Linguistics, 1994,20(4):563~596. 9  Zhou Ming, Li Sheng et al. Dear: a translator's workstation. In: Proceedings of the NLPRS'95, Natural Language Processing Pacific Rim Symposium. KPChoi: Publishing House of Korean Advance Institute of Science and Technology, Korea, 1995. 388~397
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张 民,李 生,赵铁军,张艳风.统计与规则并举的汉语词性自动标注算法.软件学报,1998,9(2):134-138

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History
  • Received:August 21,1996
  • Revised:March 20,1997
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