One major problem in multilingual Question Answering (QA) is the integration of information obtained from different languages into one single ranked list. This paper proposes two different architectures to overcome this problem. The first one performs the information merging at passage level, whereas the second does it at answer level. In both cases, we applied a set of traditional merging strategies from cross-lingual information retrieval. Experimental results evidence the appropriateness of these merging strategies for the task of multilingual QA, as well as the advantages of multilingual QA over the traditional monolingual approach.