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NLP-Driven Event Semantic Ontology Modeling for Story

  • Chun-Ming Gao
  • Qiu-Mei Xie
  • Xiao-Lan Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7934)

Abstract

This paper presents a NLP-driven semantic ontology modeling for unstructured data of Chinese children stories. We use a weakly-supervised approach to capture n-ary facts based on the output of dependency parser and regular expressions. After n-ary facts post-processing, we populate the extracted facts of events to SOSDL (Story-Oriented Semantic Language), an event ontology designed for modeling semantic elements and relations of events, to form a machine-readable format. Experiments indicate the reasonability and feasibility of our approach.

Keywords

Information Extraction Natural Language Processing N-ary Relation Event Ontology 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Chun-Ming Gao
    • 1
  • Qiu-Mei Xie
    • 1
  • Xiao-Lan Wang
    • 1
  1. 1.School of Information Science and EngineeringHunan UniversityChangshaChina

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