计算机科学 ›› 2022, Vol. 49 ›› Issue (10): 224-242.doi: 10.11896/jsjkx.211000057

• 人工智能 • 上一篇    下一篇

文档级实体关系抽取方法研究综述

冯钧, 魏大保, 苏栋, 杭婷婷, 陆佳民   

  1. 水利部水利大数据重点实验室(河海大学) 南京 211100
    河海大学计算机与信息学院 南京 211100
  • 收稿日期:2021-10-09 修回日期:2022-05-20 出版日期:2022-10-15 发布日期:2022-10-13
  • 通讯作者: 冯钧(fengjun@hhu.edu.cn)
  • 基金资助:
    国家重点研发计划(2021YFB3900601)

Survey of Document-level Entity Relation Extraction Methods

FENG Jun, WEI Da-bao, SU Dong, HANG Ting-ting, LU Jia-min   

  1. Key Laboratory of Water Big Data Technology of Ministry of Water Resources,Hohai University,Nanjing 211100,China
    School of Computer and Information College,Hohai University,Nanjing 211100,China
  • Received:2021-10-09 Revised:2022-05-20 Online:2022-10-15 Published:2022-10-13
  • About author:FENG Jun,born in 1969,Ph.D,professor,Ph.D supervisor.Her main research interests include data management,domain knowledge discovery research,and water conservancy informatization.
  • Supported by:
    National Key R&D Program of China(2021YFB3900601).

摘要: 实体关系抽取作为文本挖掘和信息抽取的核心任务,意图从自然语言文本中识别并判定实体对之间存在的特定关系,为智能检索、语义分析等提供了基础支持,有助于提高搜索效率,是自然语言处理领域中的研究热点。相比从单句中进行抽取,文档中包含了更加丰富的实体关系语义,因此近年来很多新的抽取方法纷纷将研究重点从句子层次转移到文档层次,并取得了丰富的研究成果。文中系统地总结了近年来文档级实体关系抽取的主流方法和研究进展。首先概述了文档级关系抽取问题及面临的挑战,然后从基于序列、基于图和基于预训练语言模型3个方面介绍多种文档级关系抽取方法,最后对各种方法使用的数据集及实验进行对比分析,并对未来可能的研究方向进行了探讨和展望。

关键词: 关系抽取, 文档级关系抽取, 深度学习, 图神经网络, 预训练语言模型

Abstract: As the core task of text mining and information extraction,entity relation extraction intends to identify and determine the specific relation between entity pairs from natural language texts,provides basic support for intelligent retrieval and semantic analysis,and helps to improve search efficiency.It is a research hotspot in the field of natural language processing.Compared with relation extraction from single sentence,documents contain richer entity relation semantics.Therefore,recently many new extraction methods have shifted their research focus from sentence-level to document-level,and achieved rich research results.This paper systematically summarizes the mainstream methods and research progress of document-level entity relation extraction in recent years.Firstly,the paper summarizes the problems and challenges of document-level relation extraction,and then introduces a variety of document-level relation extraction methods from three aspects:sequence based,graph based and pre-trained language model based.Finally,the data sets and experiments used by each method are compared and analyzed,and the possible research directions in the future are discussed and prospected.

Key words: Relation extraction, Document-level relation extraction, Deep learning, Graph neural network, Pre-trained language model

中图分类号: 

  • TP391
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