A Logical-Form and Knowledge-Base Design for Natural Language Generation

A LOGICAL-FORM AND KNOWLEDGE-BASE DESIGN FOR NATURAL LANGUAGE GENERATION 12 / Norman K. Sondheimer Bernhard Nebel USC/Information Sciences Institute Technische Iniversitaet Berlin Marina del Rey, CA Berlin, West Germany ABSTRACT This paper presents a technique for interpreting output demands by a natural language sentence generator in a formally transparent and efficient way. These demands are stated in a logical language. A network knowledge base organizes the concepts of the application domain into categories known to the generator. The logical expressions are interpreted by the generator using the knowledge base and a restricted, but efficient, hybrid knowledge representation system. This design has been used to allow the NIGEL generator to interpret statements in a first-order predicate calculus using the NIKL and KL-TWO knowledge representation systems. The success of this experiment has led to plans for the inclusion of this design in both the evolving Penman natural language generator and the Janus natural language interface. 1. INTRODUCTION we have as a general goal the development of natural language generation capabilities. Independent software systems will state demands to the generation facility in a mutually convenient form. The generator will use those demands to create natural language sentences. Instead of merging generation with other functions of the overall computer system, this design allows for reuse of the generator in other systems, specialized processing of linguistic information, and modular development. Our design requires a notation to represent expressive demands. The notation should be of general applicability. For example, a good notation ought to be acceptable as the output of a natural language parser. The notation should have a well-defined semantics. In addition, the generator has to have some way of interpreting the demands. This interpretation has to be efficient. In our research, we have used formal logic as a demand language. Network knowledge-bases are used to define the domain of discourse in order to help the generator interpret the logical forms. And a restricted, hybrid knowledge representation is utilized to analyze demands for expression using the knowledge base. Arguments for these decisions include the following: Formal logic is a well established means of expressing information with a well-defined semantics. Furthermore, it is commonly used in natural language analyzers and discourse processors, as well as other AI systems. Network knowledge-base notations have been shown to be effective and efficient in language processing. Work on network representations has shown that they too can be given formal semantics [Schmolze and Lipkis 83]. Finally, recent work on hybrid knowledge representation systems has shown how to combine the reasoning of logic and network systems [Brachman 85]. Restricted-reasoning hybrid systems have shown this reasoning can be done efficiently. On our project, we have: 1. Developed a demand language based on first order logic, 2. Structured a NIKL (New Implementation of KL-ONE) network [Kaczmarek 86] to reflect conceptual distinctions observed by functional systemic linguists. 3. Developed a method for translation of expression demands into a propositional logic database, 4. Employed KL-TWO [Vilain 85] to analyze the translated demands, and 5. Used the …

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