ExaminingCf-ranking Methods for Text Structuring and Pronominalization in Korean

作     者：JI-EUN ROH JONG-HYEOK LEE 

作者机构：Division of Electrical and Computer Engineering Pohang University of Science and Technology (POSTECH) Advanced Information Technology Research Center (AITrc) PIRL 323 Pohang University of Science and Technology San 31 Hyoja-dong Nam-gu Pohang 790-784 Korea 

出 版 物：《International Journal of Computer Processing of Languages》 

年 卷 期：2006年第19卷第1期

页      面：39-61页

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Centering Theory Cf -ranking Text structuring Centering-based coherence metrics Pronominalization Zero pronoun 

摘      要：Centering Theory assumes that entities realized in an utterance can be ranked according to their relative salience degree. This ranking called Cf -ranking (ranking of forward-looking centers) determines the likelihood that the entities realized in an utterance will be the center of the subsequent utterance, and it is one of the central issues in Centering literatures. This paper deals with these Cf -ranking issues in Korean at the level of text structuring and pronominalization for coherent text generation. For text structuring, we compare several Cf -ranking methods by examining various Centering-based metrics to evaluate local coherence of text, and for pronominalization, we compare them by examining previous rules for Centering-based pronoun generation rules and our pronominalization model. In almost all previous works, surface word order was not solely employed for Cf -ranking, instead it was additionally considered to supplement the main ranking scheme based on the fact that linear order does not perform well alone. However, this study shows that due to the characteristics of the Korean language, ranking by surface word order is better than any other ranking method in most Centering-based Metrics which depend on Cf -ranking, and it is also reliable in terms of pronominalization accuracy. Additionally we found that based on the Cf -ranking by surface word order, it is the most effective way for text structuring to maximize simply the number of utterance pairs whose first realized nominal entity in adjacent utterances is identical.