Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (9): 168-174.DOI: 10.3778/j.issn.1002-8331.1901-0151

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Research on Joint Extraction of Triggers and Attribute-Value Pairs

WANG Yinghuan, XUE Chan, BAO Xianyu, WU Gongqing   

  1. 1.School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230601, China
    2.Shenzhen Academy of Inspection and Quarantine, Shenzhen, Guangdong 518045, China
  • Online:2020-05-01 Published:2020-04-29



  1. 1.合肥工业大学 计算机与信息学院,合肥 230601
    2.深圳市检验检疫科学研究院,广东 深圳 518045


Traditional attribute-value pair extraction methods are usually applied to short texts, and are limited to extract string attributes. In this work, a joint extraction of triggers and attribute-value pairs is proposed. The method not only can use triggers to obtain information sentences from long texts for identifying semantic attributes, but also can make full use of the interdependence among of trigger, attributes and values. Based on conditional random field a joint labeling model is Constructed to improve the extraction performance of string attribute-value pairs. Experimental results show that comparing with traditional methods, the proposed method can extract semantic attributes and improve the precision, recall and F-measure of string attributes by 15.3%, 15.5% and 15.5% respectively. At the same time, the average time of extraction is reduced by 76.29%.

Key words: conditional random field, sequence labeling, attribute-value pair extraction, trigger extension



关键词: 条件随机场, 序列标注, 属性值对抽取, 触发词扩展