Identifying Prepositional Phrases in Chinese Patent Texts with Rule-based and CRF Methods

نویسندگان

  • Hongzheng Li
  • Yaohong Jin
چکیده

Identification of prepositional phrases (PP) has been an issue in the field of Natural Language Processing (NLP). In this paper, towards Chinese patent texts, we present a rule-based method and a CRF-based method to identify the PPs. In the rule-based method, according to the special features and expressions of PPs, we manually write targeted formal identification rules; in the CRF approach, after labelling the sentences with features, a typical CRF toolkit is exploited to train the model for identifying PPs. We then conduct some experiments to test the performance of the two methods, and final precision rates are over 90%, indicating the proposed methods are effective and feasible.

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تاریخ انتشار 2015