MFC: a method of co-referent relation acquisition from large-scale chinese corpora

Authors:
Guogang Tian;Cungen Cao;Lei Liu;Haitao Wang
Affiliations:
Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences
Venue:
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
Year:
2006

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Abstract

This paper proposes a multi-feature constrained method (MFC) to acquire co-referent relations from large-scale Chinese corpora. The MFC has two phases: candidate relations extraction and verification. The extraction phase uses distribution distance, pattern homogeneity and coordination distribution features of co-referent target words to extract candidate relations from Chinese corpora. In the verification phase, we define an ontology for co-referent token words, and build a relation graph for all candidate relations. Both the ontology and the graph are integrated to generate individual, joint and reinforced strategies to verify candidate relations. Comprehensive experiments have shown that the MFC is practical, and can also be extended to acquire other types of relations.