Research of Entity Relation Extraction Model Based on Dependency Parsing Neural Network

  • Guojin CaoEmail author
  • Jianxia Chen
  • Fan Yang
  • Chao Li
  • Jie Zhang
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1075)


Relation entity extraction is an important research topic in the field of information extraction. The paper proposes an entity relation extraction model based on dependency parsing neural network, in which the dependency relations between sentences are analyzed via dependency parsing, and reveal the syntactic structure of the sentence. Experiments on several data sets show that the proposed model can improves the accuracy by 15% compared with the other method for the Chinese entity relation extraction.


Word segmentation Entity relation extraction Dependency parsing 



This research is supported by 2017CFB326 grants from Natural Science Foundation of Science and Technology Department of the Hubei Province.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Guojin Cao
    • 1
    Email author
  • Jianxia Chen
    • 1
  • Fan Yang
    • 1
  • Chao Li
    • 1
  • Jie Zhang
    • 2
  1. 1.School of Computer ScienceHubei Technology of UniversityWuhanChina
  2. 2.School of Electrical and Electronic EngineeringHubei Technology of UniversityWuhanChina

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