Discourse is a literary form that consists of semantically-related and well-structured arguments. One of the key tasks of discourse analysis is to resolve semantic relationship between arguments. Explicit relation is easy to detect with an accuracy of nearly 90% because of its direct cues. In contrast, implicit relation is difficult to detect with only an accuracy of nearly 40% since it has no direct cues. To solve the problem, paper proposes a hypothesis that parallel arguments normally have the consistent semantic relations. Based on the hypothesis and by utilizing the characteristics that explicit relation is easy to detect, the paper implements a method of implicit relation detection which uses explicit relation to infer implicit relation among parallel arguments. We evaluate the method on the standard penn discourse Treebank (PDTB). The experimental results show an improvement of 17.26%.