Addressing the task of acquiring semantic relations between events from a large corpus, we first argue the complementarity between the pattern-based relation-oriented approach and the anchor-based argumentoriented approach. We then propose a twophased approach, which first uses lexicosyntactic patterns to acquire predicate pairs and then uses two types of anchors to identify shared arguments. The present results of our empirical evaluation on a large-scale Japanese Web corpus have shown that (a) the anchor-based filtering extensively improves the accuracy of predicate pair acquisition, (b) the two types of anchors are almost equally contributive and combining them improves recall without losing accuracy, and (c) the anchor-based method also achieves high accuracy in shared argument identification.