Abstract
As the first step of temporal information understanding, the results of temporal expressions recognition will directly affect further usage of temporal information. For Chinese language, there are many distinct characters both in word morphology and syntax in temporal expressions compared with the Western languages. Classifications and constructions of Chinese temporal expressions were analysed, and an approach for extracting temporal expressions from Chinese texts was presented in this paper. The model comprises of a cascade of rule-based and machine-learning pattern recognition procedures. Conditional random fields (CRFs) were applied to recognise time units rather than time expressions to avoid the boundary localisation problems in Chinese temporal expressions. Rules for the temporal expressions boundary localisation were formulated based on time triggers thesaurus and time affix words thesaurus. The F-measure of temporal expressions identification was 95.93% on the temporal 2010 Chinese corpus. The experiments result showed the validity of the proposed approach.
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