Report Number: CS-TR-78-668
Institution: Stanford University, Department of Computer Science
Title: BAOBAB, a parser for a rule-based system using a semantic grammar
Author: Bonnet, Alain
Date: September 1978
Abstract: Until a recent knowledge-based system is able to learn by itself, it must acquire new knowledge and new heuristics from human experts. This is traditionally done with the aid of a computer programmer acting as intermediary. The direct transfer of knowledge from an expert to the system requires a natural-language processor capable of handling a substantial subset of English. The development of such a natural-language processor is a long-term goal of automating knowledge acquisition; facilitating the interface between the expert and the system is a first step toward this goal. This paper descrtbes BAOBAB, a program designed and implemented for MYCIN (Shortliffe 1974), a medical consultation system for infectious disease diagnosis and therapy selection. BAOBAB is concerned with the problem of parsing - recognizing natural language sentences and encoding them into MYClN's internal representation. For this purpose, it uses a semantic grammar in which the non-terminal symbols denote semantic categories (e.g., infections and symptoms), or conceptual categorles whlch are common tools of knowledge representation in artificial intelligence (e.g., attributes, objects, values and predicate functions). This differs from a syntactic grammar in which non-terminal symbols are syntactic elements such as nouns or verbs.