Acquiring ISA Relations from Chinese Free Text Based on Multiple Patterns

Abstract

Automatic acquisition of ISA relations is a basic problem in knowledge acquisition from text. We present a method that acquires and verifies ISA relations from large Chinese free text. It initially discovers a set of sentences using Chinese lexicosyntactic patterns. Then we combine outside layer removal and inside layer gathering for acquiring concepts of constituting ISA relation. Finally, ISA relations are verified with semantic features and context features. The experimental results show the efficiency of our method.