JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2017, Vol. 52 ›› Issue (9): 7-12.doi: 10.6040/j.issn.1671-9352.1.2016.PC7

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Chinese entity relation extraction algorithms based on COAE2016 datasets

SUN Jian-dong, GU Xiu-sen, LI Yan, XU Wei-ran*   

  1. Beijing University of Posts and Telecommunications, Lab of Pattern Recognition and Intelligent System, Beijing 100876, China
  • Received:2016-11-25 Online:2017-09-20 Published:2017-09-15

Abstract: Entity relation extraction is one of the important procedures of knowledge graph technology. Research on entity relation extraction in English is comparatively developed. By contrast, the development of Chinese entity relation extraction is not ideal, and it is mainly because the lack of corpus. In order to solve this problem, COAE2016 proposes a Chinese entity relation extraction task in task 3. In this paper, we use three algorithms to solve the problem: a pattern based algorithm, a SVM based algorithm and a CNN based algorithm respectively. Then, we analyze the advantages and the disadvantages of the three algorithms according to the effects of the dataset in COAE2016 Experiments show that the SVM based algorithm and the CNN based algorithm are useful to extract entity relation.

Key words: feature extraction, SVM, CNN, pattern match

CLC Number: 

  • TP391
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