Recognizing the Extent of Chinese Time Expressions Based on the Dependency Parsing and Error-Driven Learning
Sheng Li · Zhongwen xinxi xuebao · 2007
Recognizing time expressions is the foundation of its normalization,and its performance directly influences the robustness of the normalization.This paper proposes a new method for recognizing the extents of the time expressions based on dependency parsing and error-driven learning,which begins with time trigger word(namely,the syntactic head of dependency relation),uses Chinese dependency parsing to recognize the extents of the time expressions,Subsequently,we use the transformation-based error-driven learning to improve the performance.,which can automatically acquire and modify the rules and get 3.5% increase after applying the learned rules.Finally,F1 = 76.38% and F1 =76.57% results are obtained on the closed and the open test set respectively.