Chinese Negation and Speculation Detection with Conditional Random Fields
Negative and speculative expressions are popular in natural language.Recently, negation and speculation detection has become an impor tant task in computational linguistics community.However, there are few re lated research on Chinese negation and speculation detection.In this paper, a supervised machine learning method with conditional random fields (CRFs) is proposed to detect negative and speculative information in scientific litera ture.This paper also evaluates the effectiveness of each feature under the character-based and word-based framework, as well as the combination of features.Experimental results show that the single-word feature and the part of speech feature are effective, and the combined features improve the per formance furthest.Our Chinese negation and speculation detection system in sentence level achieves 94.70% and 87.10% of accuracy, respectively.
negation speculation conditional random fields
Zhancheng Chen Bowei Zou Qiaoming Zhu Peifeng Li
Natural Language Processing Lab, Soochow University, Suzhou, Jiangsu, 215006 School of Computer Science & Technology, Soochow University, Suzhou, Jiangsu, 215006
国际会议
Second CCF Conference,NLPCC2013(第二届自然语言处理与中文计算会议)
重庆
英文
30-40
2013-11-15（万方平台首次上网日期，不代表论文的发表时间）