A Problem Solving Approach to Generating Text From Systemic Grammars

A PROBLEM SOLVING APPROACH TO GENERATING TEXT FROM SYSTEMIC GRAMMARS* Terry Patten Dept. of Artificial Intelligence, University of Edinburgh Hope Park Square, Meadow Lane, EH8 9NW. ABSTRACT Systemic grammar has been used for AI text generation work in the past, but the Implementa- tions have tended be ad hoc or inefficient. This paper presents an approach to systemic text genera- tion where AI problem solving techniques are applied directly to an unadulterated systemic gram- mar. This approach is made possible by a special relationship between systemic grammar and problem solving: both are organized primarily as choosing from alternatives. The result is simple, efficient text generation firmly based in a linguistic theory. INTRODUCTION This paper will describe an approach to text generation where AI problem solving techniques are used to generate text from systemic grammars.** Problem solving is a general term used here to refer to areas of AI research such as 'expert sys- tems', 'planning', 'design' and so on [Hayes-Roth et al., 1983). Techniques developed in these fields are applied directly to an unadulterated systemic grammar, resulting in a simple, efficient text generator firmly based in an established linguistic theory. This approach is only possible because of a fundamental relationship that exists between sys- temic grammar and AI problem solving. This relationship is described in the next section. The third section will be concerned with one of the most important manifestations of this special rela- tionship: a common representation. The following section will show how this common representation allows goal directed problem solving techniques to be aPPlied directly to the grammar. One of the most novel and important aspects of this approach is that it is compatible with the semantic stratum described in the systemic theory: a system network organized around the idea of 'register' {Halliday, 1978). The semantic stratum and its relationship to the grammar will be discussed next. Some advan- tages of the approach will then be put forward. * Many thanks to my supervisors Graeme Ritchie and Austin Tare. This work was supported in part by an ORS award. ** For an overview of systemic grammar, see [Winograd, 1983] Chapter 6. Finally, the current status of the project will be described, including sample output generated from a large grammar. THE FUNDAMENTAL RELATIONSHIP I. "The central nature of intelligent Problem solving is that a system must construct its solution selectively and efficiently from a space of aiterna- tlves." [Hayes-Roth et al., 1983) 2. "We shall define language as 'meaning potential': that is as sets of options or alternatives, in meaning, that are avail- able to the speaker-hearer." [Halliday in deJoia et al., 1980, I~72) Compare these two quotations. Notice that both AI problem solving and systemic grammar have at their very core the idea of choosing from alterna- tives. Systemic grammar is probably unique in hav- ing such emphasis on the idea of choice; or in dif- ferent terminology, systemic grammar is dis- tinguished in allowing the paradigmatic mode of description to dominate over the syntagmatic [see Halliday …

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