What do you mean “null”? Turning null responses into quality responses

When natural language front-ends are introduced to database management systems, generation of quality responses have proven problematical in situations when null values arise. In our work, in which we assume the database query language is SQL, we present methods for responding with appropriate answers to null value responses. To do so we use a knowledge base based on RM/T, an extended relational model proposed by E. F. Codd. The advantages of this approach are described. To demonstrate the utility of the knowledge base, a simple knowledge base is constructed. A detailed algorithm is given to provide additional information when a null answer is returned.