  General natural dialogue processing requires large amounts of domain
knowledge as well as linguistic knowledge in order to ensure acceptable
coverage and understanding. There are several ways of integrating lexical
resources (e.g. dictionaries, thesauri) and knowledge bases or ontologies at
different levels of dialogue processing. We concentrate in this paper on how to
exploit domain knowledge for filtering interpretation hypotheses generated by a
robust semantic parser. We use domain knowledge to semantically constrain the
hypothesis space. Moreover, adding an inference mechanism allows us to complete
the interpretation when information is not explicitly available. Further, we
discuss briefly how this can be generalized towards a predictive natural
interactive system.
