A text knowledge base from the AI handbook

Abstract

This research aims at defining a consistent set of text representation conventions for organizing fifty pages of the AI handbook as an inferential knowledge base founded on a procedural logic system of general inference schemes for answering questions from it. As a result of research on the AI handbook project, we have developed a prototype, natural-language, text-knowledge system that includes a data base manager to compile the text knowledge and to make it available to navigational commands. The text is represented as logical propositions that form a set of text axioms to model its content. English questions and commands are translated to corresponding logical formulas and treated as theorems to be proved with respect to the text model. The logical form is that of semantic relations (SRs)—logical predicates with varying numbers and ordering of arguments. To compute effectively with such a free form, a relaxed unification procedure was defined as the basis of the SR theorem prover. The use of procedural logic, augmented with fast compiled LISP functions, has shown that questions can be answered in times ranging from a few tenths of a second to minutes of CPU time on a DEC2060 system. The navigational capabilities of the data base manager make available larger contexts surrounding the text and offer the user complete freedom to explore the text and to extract any desired information from it.