The Field of Automatic Entity Relation Extraction Based on Binary Classifier and Reasoning

  • Authors:
  • Chun-ya Lei;Jian-yi Guo;Zheng-tao Yu;Shao-min Zhang;Cun-li Mao;Chao-shen Zhang

  • Affiliations:
  • -;-;-;-;-;-

  • Venue:
  • ISIP '10 Proceedings of the 2010 Third International Symposium on Information Processing
  • Year:
  • 2010

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Abstract

To solve the difficulty of the field of Automatic Entity Relation Extraction, in this paper, a method that used binary classification thinking, meanwhile combined with reasoning rules to extract the field of entity relation is proposed. considering comprehensively the context information of entity, entity type and their combination of characteristics to construct the feature set, which in order to build the Binary Classifier of entity relation extraction, then taking full advantage of the field characteristics of entity relation, further combine reasoning rules to obtain the type of the field of entity relation. Doing our experiment on the artificial collection of 600 corpuses for tourism field, experimental result shows the method of Binary Classifier combining Reasoning is better than Multiple Classifiers, the F-score is improved 3%.