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Person-relation extraction using bert based knowledge graph

Authors
Yang S.M.Yoo S.Y.Ahn Y.S.Jeong O.R.
Issue Date
Jun-2020
Publisher
ICIC International
Keywords
Knowledge graph; Named entity recognition; Relation extraction
Citation
ICIC Express Letters, Part B: Applications, v.11, no.6, pp.539 - 544
Journal Title
ICIC Express Letters, Part B: Applications
Volume
11
Number
6
Start Page
539
End Page
544
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/52281
DOI
10.24507/icicelb.11.06.539
ISSN
2185-2766
Abstract
Artificial intelligence technology has been actively researched in the areas of image processing and natural language processing. Recently, with the release of Google’s language model BERT, the importance of artificial intelligence models has attracted attention in the field of natural language processing. In this paper, we propose a knowledge graph to build a model that can extract people in a document using BERT, and to grasp the relationship between people based on the model. In addition, to verify the applicability of person extraction techniques using BERT based knowledge graphs, we conduct a performance comparison experiment with other person extraction models and apply our proposed method to the case study. © 2020, ICIC International.
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