In this paper, we study the problem of adding a large number of new words into a Chinese thesaurus according to their definitions in a Chinese dictionary, while minimizing the effort of hand tagging. To deal with the problem, we first make use of a kind of supervised learning technique to learn a set of defining formats for each class in the thesaurus, which tries to characterize the regularities about the definitions of the words in the class. We then use traditional techniques in Graph theory to derive a minimal subset of the new words to be added into the thesaurus, which meets the following condition: if we add the new words in the subset into the thesaurus by hand, the other new words can be added into the thesaurus automatically by matching their definitions with the defining formats of each class in the thesaurus. The method uses little, if any, language-specific or thesaurus-specific knowledge, and can be applied to the thesauri of other languages.