Many of the recent advances in artificial intelligence (Al) have been brought about through the use of domain specific knowledge. In this same spirit, this paper presents an approach to understanding natural language data base queries that employs the use of domain specific knowledge to aid the parsing process. The unique aspect of 1he data base query environment relative to other AI problem domains is that the required body of knowledge already exists in the form of the data base being queried. Thus, there is an important benefit of making use of this knowledge in the form in which it is maintained by the data base management system, since the very difficult problems of gathering and representing this information can be circumvented.

The paper describes the problems encountered in the parsing of data base queries that can be solved by the semantic use of the data base, as well as a precise description of how these problems can be solved by existing data base systems.

The proposed use of the data base as a semantic component has been a primary component of the design of a high performance natural language data base query system called ROBOT, that has been successfully installed at several commercial installations. Since this system is a physical realization of the proposed methodology, a brief description of the system and its experiences in the field are given as evidence of the feasibility of this approach.