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Systemic text generation as problem solving

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Systemic text generation as problem solving

An exploration of a new approach to text generation that interprets systemic grammar as a computational representation. Patten demonstrates that systemic grammar can be easily and automatically translated into current AI-knowledge representations and efficiently processed by the same knowledge-based techniques currently exploited by expert systems. Thus, the fundamental methodological problem of interfacing specialized computational representations with equally specialized linguisticrepresentations can be resolved. The study provides a detailed discussion of the formal model proposed and of a substantial implementation including a relatively large systemic grammar. It represents a fundamental and productive contribution to the literature of text generation.
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