Chinese Pronominal Anaphora Resolution Based on Conditional Random Fields

Author

Fei, Li ; Shuicai, Shi ; Yuzhong, Chen ; Xueqiang, Lv

Author_Institution

Chinese Inf. Process. Res. Center, Beijing Inf. Sci. & Technol. Univ., Beijing

Volume

1

fYear

2008

fDate

12-14 Dec. 2008

Firstpage

731

Lastpage

734

Abstract

Anaphora resolution plays an important role in nature language processing. According to features of Chinese personal pronoun, we present an approach which adopts Conditional Random Fields to do anaphora resolution of personal pronoun in Chinese texts. The method takes into account all kinds of anaphoric features and those effects among each other. The experimental results on the Chinese ACE training corpus demonstrate that the proposed method is feasible for the anaphora resolution of Chinese personal pronoun.

Keywords

learning (artificial intelligence); linguistics; natural language processing; random processes; text analysis; Chinese personal pronoun; Chinese pronominal anaphora resolution; Chinese text; conditional random field; machine learning method; nature language processing; Computer science; Entropy; Graphical models; Hidden Markov models; Information processing; Information technology; Natural language processing; Natural languages; Software engineering; Standardization; Anaphora Resolution; Conditional Random Fields; Natural Language Processing; Personal Pronoun;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Software Engineering, 2008 International Conference on

Conference_Location

Wuhan, Hubei

Print_ISBN

978-0-7695-3336-0

Type

conf

DOI

10.1109/CSSE.2008.432

Filename

4721853