JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2015, Vol. 45 ›› Issue (6): 7-15.doi: 10.6040/j.issn.1672-3961.2.2015.085

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Chinese entity relation extraction based on entity semantic similarity

XU Qing1, DUAN Liguo1, LI Aiping1,2, YIN Guimei3   

  1. 1. College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, Shanxi, China;
    2. State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, Hubei, China;
    3. Department of Computer Science and Technology, Taiyuan Normal University, Taiyuan 030600, Shanxi, China
  • Received:2015-05-18 Revised:2015-10-26 Online:2015-12-20 Published:2015-05-18

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Abstract: In order to explore the impact of the semantic similarity on the Chinese entity relation extraction, two new features were proposed, which were the "TongYiCi Cilin" code tree constructed with the entities'5 layer code in "TongYiCi Cilin" and the entity semantic similarity tree constructed with the average of the semantic similarity between the entity word in relation instance and all entity words in each category of relation. The impact on the relation extraction performance of these two new features together with the existing "TongYiCi Cilin" code feature and the entity type information feature was explored. In the cases with single features, the entity type feature got the best performance, and the F values of subtype and type were 84.9 and 83.2; In the cases with combination features, the combination of the entity type feature and the "TongYiCi Cilin" code tree feature got the best performance, the F values of both subtype and type were 2.5 higher than the entity type feature. But the performance of three combinations features became poorer instead of better. The results showed that the "TongYiCi Cilin" code tree was an effective supplement of the entity type information, but excessive features may result in information redundancy and poor performance.

Key words: syntax tree, semantic similarity, tree kernel, TongYiCi CiLin, Chinese entity relation extraction

CLC Number: 

  • TP391.1
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