Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (8): 220-225.DOI: 10.3778/j.issn.1002-8331.1611-0326

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Extraction of non-taxonomic relations based on SAO structure

MA Xun1, ZHOU Changsheng2, LV Xueqiang1, ZHOU Jianshe3   

  1. 1.Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing Information Science & Technology University, Beijing 100101, China
    2.Computing Center, Beijing Information Science & Technology University, Beijing 100192, China
    3.Beijing Advanced Innovation Center for Imaging Technology, Capital Normal University, Beijing 100048, China
  • Online:2018-04-15 Published:2018-05-02

基于SAO结构的非分类关系抽取研究

马  勋1,周长胜2,吕学强1,周建设3   

  1. 1.北京信息科技大学 网络文化与数字传播北京市重点实验室,北京 100101
    2.北京信息科技大学 计算中心,北京 100192
    3.首都师范大学 北京成像技术高精尖创新中心,北京 100048

Abstract: In order to solve the problem of relation recognition in the extraction of the non-taxonomic relation, this paper proposes a recognition method that combines the Subject-Action-Object(SAO) structure and the dependency syntax. The method transforms the extraction of the non-taxonomic relation in Chinese patent domain into the recognition problem of SAO structure. The recognition problem of relation can be solved by the verbs information in the SAO structure, and on this basis, the traditional features are combined with the dependency strength that is gotten from the dependency syntax. And then, the validity of new features, word features, context features and distance features are verified and analyzed. The experimental results not only indicate that this method is superior to traditional methods, but also verify the feasibility of the dependency syntax in the extraction of the non-taxonomic relation.

Key words: Subject-Action-Object(SAO) structure, non-taxonomic relation, relation extraction, dependency syntax

摘要: 针对非分类关系抽取中的关系识别问题,提出利用SAO结构和依存句法分析相结合的识别方法。该方法将中文专利领域的非分类关系抽取问题转化为符合SAO结构的识别问题,通过SAO结构中的动词信息可以解决关系识别的问题,并在此基础上,利用依存句法分析得到的依存关系强度结合传统的特征,分别对新特征、词特征、上下文特征、距离特征的有效性进行验证分析。实验结果表明,该方法优于传统方法,也验证了依存句法分析在非分类关系抽取中的可行性。

关键词: SAO结构, 非分类关系, 关系抽取, 依存句法