This paper extends our work on natural language understanding (NLU) using Belief Networks, as proposed in [1]. We have previously devised a method for identifying the user’s communicative goal(s) out of a finite set of domain-specific goals. The problem was formulated as making N binary decisions, each performed by a Belief Network (BN). This formulation allows for the identification of queries with multiple goals, as well as queries with out-of-domain (OOD) goals. Our current work presents two extensions: (i) migrating our investigation from English to Chinese; and (ii) exploring the alternate formulation of goal identification as making one N-ary decision by a single BN. Experiments with the AITS (Air Travel Information System) corpus showed that the N-ary formulation improved over the N binary formulation in terms of single/multiple goal identification accuracies and OOD rejection.