The case postpositions usually have more than one semantic role in Korean. The adverbial postpositions among various postpositions especially make the development of Korean-based machine translation system difficult, because they have more semantic roles than others. In this paper, we describe a new method for resolving semantic ambiguities of adverbial postpositions using decision tree induction. The lack of training examples in decision tree induction is overcome by clustering words into classes using a kind of greedy algorithm. The cross validation results show that the presented method achieves 76.5% of accuracy on the average, which is 20.3% improvement over the baseline method.