Hybrid learning of Syntactic and Semantic Dependencies


  •  Lin Yao    
  •  Chengjie Sun    
  •  Lu Li    
  •  Zhixin Hao    
  •  Xiaolong Wang    

Abstract

This paper presents our solution for jointly parsing of syntactic and semantic dependencies. The Maximum Entropy (ME) classifier is selected in this system. Also the Mutual Information (MI) model was utilized into feature selection of dependency labeling. Results show that the MI model allows the system to get better performance and reduce training hours.


This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1913-8989
  • ISSN(Online): 1913-8997
  • Started: 2008
  • Frequency: quarterly

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