We describe Scusi?, a multi-stage, spoken language interpretation mechanism designed to be part of a robotmounted dialogue system. Scusi??s interpretation process maps spoken utterances to conceptual graphs, and the nodes in these graphs to concepts in the world. Maximum posterior probability is used to rank the (partial) interpretations produced at each stage of this process. We show how the features of our interpretation process yield desirable behaviours that support robust and flexible system performance.