计算机科学 ›› 2016, Vol. 43 ›› Issue (2): 31-34, 56.doi: 10.11896/j.issn.1002-137X.2016.02.006

• 2015年中国计算机学会人工智能会议 • 上一篇    下一篇

中文指代消解模型的对比研究

周炫余,刘娟,罗飞,刘洋,颜晗   

  1. 武汉大学计算机学院 武汉430072,武汉大学计算机学院 武汉430072,武汉大学计算机学院 武汉430072,武汉大学计算机学院 武汉430072,武汉大学计算机学院 武汉430072
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金(61272274),国家自然科学基金青年项目(61402340),湖北省自然科学基金青年项目(2014CFB194)资助

Comparison of Chinese Anaphora Resolution Models

ZHOU Xuan-yu, LIU Juan, LUO Fei, LIU Yang and YAN Han   

  • Online:2018-12-01 Published:2018-12-01

摘要: 指代消解的基本任务是把指向现实世界中相同实体的所有实体表达关联起来。与英文指代消解的研究相比,中文指代消解的研究相对较少,至今没有对现存的中文指代消解模型进行公平的测评和比较,主要原因是现存的中文指代消解模型在训练和测评时采用了不同的语料,且所选用的特征属性也不相同。基于上述原因,实现了5类基本的中文指代消解模型,并在ACE2005中文语料上进行同平台、同语料、同特征的测评。通过测评比较了各类模型的性能,同时分析和探讨了影响中文指代消解模型精度的各种因素。

关键词: 人工智能,指代消解模型,指代消解,自然语言处理

Abstract: The task of anaphora resolution is determining linguistic expressions that refer to the same real-world entity in a text.Compared to the amount of research on English anaphora resolution,relatively little work has been done on Chinese anaphora resolution.To our best knowleage,there is no fair comparison on the Chinese anaphora resolution models,mainly because of the useage of different data and features.We aimed to gain insights into the factors that affect the performance of the models and the advantages of each model via experiment with the same data and features in the ACE2005 Chinese corpus.

Key words: Artificial intelligence,Anaphora resolution models,Anaphora resolution,Natural language processing

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