Indirect responses to loaded questions

Casual users of Natural Language (NL) computer systems are typically inexpert not only with regard to the technical details of the underlying programs, but often with regard to the structure and/or content of the domain of discourse. Consequently, NL systems must be designed to respond appropriately when they can detect a misconception on the part of the user. Several conventions exist in cooperative conversation that allow a speaker to indirectly encode their intentions and beliefs about the domain into their utterances, ("loading" the utterances), and allow (in fact, often require) a cooperative respondent to address those intentions and beliefs beyond a literal, direct response. To be effective, NL computer systems must do the same. The problem, then, is to provide practical computational tools which will determine both when an indirect response is required, and wh-~ that response should be, without requiring that large amounts of domain dependent world knowledge be encoded in special formalisms. This paper will take the position that distinguishing language driven inferences from domain driven inferences provides a framewor-~r a s--~ution to this problem in the Data Base (DB) query domain. An implemented query system (CO-OP) is described that uses this distinction to provide cooperative responses to DB queries, using only a standard (CODASYL) DB and a lexicon as sources of world knowledge.