计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (18): 153-156.

• 数据库、信号与信息处理 • 上一篇    下一篇

语义角色标注中有效的识别论元算法研究

丁金涛1,2,周国栋1,2,王红玲1,2,朱巧明1,2   

  1. 1.苏州大学 计算机科学与技术学院,江苏 苏州 215006
    2.江苏省计算机信息处理技术重点实验室,江苏 苏州 215006
  • 收稿日期:2008-01-07 修回日期:2008-03-26 出版日期:2008-06-21 发布日期:2008-06-21
  • 通讯作者: 丁金涛

Research of effective argument identification algorithm in semantic role labeling

DING Jin-tao1,2,ZHOU Guo-dong1,2,WANG Hong-ling1,2,ZHU Qiao-ming1,2   

  1. 1.School of Computer Science and Technology,Soochow University,Suzhou,Jiangsu 215006,China
    2.Jiangsu Provincial Key Laboratory of Computer Information Processing Technology,Suzhou,Jiangsu 215006,China
  • Received:2008-01-07 Revised:2008-03-26 Online:2008-06-21 Published:2008-06-21
  • Contact: DING Jin-tao

摘要: 语义角色标注中论元识别的结果对论元分类任务起着很重要的作用。以句法成分的中心词为依据,对论元识别算法进行研究,在训练集上识别出了98.78%的论元,在测试集识别出了97.17%的论元,并大大减少了不承担角色的训练样例。在此基础上以句法成分为标注单元,在自动句法分析上抽取和组合有用的特征,用支持向量机的方法进行学习分类,在测试集上获得77.84%的F1值。此结果是目前报告的基于单一句法分析的最好结果之一。

Abstract: Argument identification plays an important role for argument classification task in semantic role labeling.According to the headwords of the constituents,this paper researches on argument identification algorithm.The experiment shows that 98.78% of arguments on train set and 97.17% on test set are identified.At the same time,most of NULL arguments are pruned.The existed features are re-combined and optimized to capture more useful information.A SVM classifier is used in the semantic role labeling system,which took syntactic constituents as labeled units.The F1-score of SRL on test set achieves 77.84%.So far as it is known,it is one of the best result based on single syntactic parser in literatures.