Chinese Temporal Phrase Recognition Based on Conditional Random Fields
Shasha Zhu, Zongtian Liu, Jianfeng Fu, Fang Zhu · Jisuanji gongcheng · 2011
(Abstract )With complex and diverse language forms, temporal phrases are not perfectly recognized by traditional rule-based method. It is hard to extract an exact match for temporal phrases and recognize the long-distance-dependent temporal phrases representing time with many tokens in Chinese text. To solve these issues, based on the capability to integrate different levels features of Conditional Random Fields(CRFs) model, this paper presents a CRFs-based approach for temporal phrases recognition. By analyzing a set of linguistic features of time phrases in Chinese text such as lexical features, syntactic features and context information, temporal phrases are divided into two types, time-denoting temporal phrases and event-denoting temporal phrases. Three common vocabularies are semi-auto structured as external features. Experimental results show a performance reaching scores of 95.70 % for F-measure to time-denoting temporal phrases and 85.75 % for F-measure to event-denoting temporal