Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 4
1004-1007,1021

Joint extraction method of entity and relationship based on pointer network

Wang Yongchaoa
Mu Hualingb
Zhou Lingzhib
Xing Weib
a. Center of Information & Technology, b. College of Computer Science, Zhejiang University, Hangzhou 310027, China
DOI: 10.19734/j.issn.1001-3695.2020.04.0113

Abstract

In order to solve the problems of insufficient modeling of entity and relationship dependence and the difficulty of extracting multiple relationships involved in existing joint extraction methods of entities and relationships, this paper designed a joint extraction framework based on deep learning. Firstly, for the problem of insufficient dependency modeling, the framework extracted entity co-occurrence features from the pre-trained corpus, and modeled the potential semantic relationship between entities and the dependency relationship between entities and relationships. Secondly, it included a novel pointer labeling method. This labeling method could represent the relationship category through a pointer. Since any entity could be pointed by multiple pointers, it was possible to mark overlapping entities in a piece of text and extracted multiple entity-relation triplets result. Finally, in order to effectively use the rich semantics of words and the information dependent on pointers, it designed a tag-aware attention mechanism was necessary, which incorporated word information from the coding layer and related co-occurrence semantic information. Compared with the joint extraction method at the forefront of research, the proposed method achieved an increase in F1 value on the Baidu DuIE test set. The experimental results show that the pointer labeling method can solve the problem of entity overlap to a certain extent.

Foundation Support

国家重点研发计划资助项目(2019YFC1521304,2020YFC1523101)
浙江省重点研发计划资助项目(2018C03051,2021C03140)
石窟寺文物数字化保护国家文物局重点科研基地资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.04.0113
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 4
Section: Algorithm Research & Explore
Pages: 1004-1007,1021
Serial Number: 1001-3695(2021)04-007-1004-04

Publish History

[2021-04-05] Printed Article

Cite This Article

王勇超, 穆华岭, 周灵智, 等. 基于指针网络的实体与关系联合抽取方法 [J]. 计算机应用研究, 2021, 38 (4): 1004-1007,1021. (Wang Yongchao, Mu Hualing, Zhou Lingzhi, et al. Joint extraction method of entity and relationship based on pointer network [J]. Application Research of Computers, 2021, 38 (4): 1004-1007,1021. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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