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In example-based NLP, the problem of computational cost of example retrieval is severe, since the retrieval time increases in proportion to the number of examples in the database. This paper proposes a novel example retrieval method for avoiding full retrieval of examples. The proposed method has the following three features, 1) it generates retrieval queries from similarities, 2) efficient example retrieval through the tree structure of a thesaurus, 3) binary search along subsumption ordering of retrieval queries. Example retrieval time drastically decreases with the method.

Thesaurus-based efficient example retrieval by generating retrieval queries from similarities