Paper: Hybrid Methods For POS Guessing Of Chinese Unknown Words

ACL ID P05-2001
Title Hybrid Methods For POS Guessing Of Chinese Unknown Words
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2005
Authors

This paper describes a hybrid model that combines a rule-based model with two statistical models for the task of POS guessing of Chinese unknown words. The rule-based model is sensitive to the type, length, and internal structure of unknown words, and the two statistical models uti- lize contextual information and the like- lihood for a character to appear in a par- ticular position of words of a particular length and POS category. By combining models that use different sources of infor- mation, the hybrid model achieves a pre- cision of 89%, a significant improvement over the best result reported in previous studies, which was 69%.