This study explores an approach to text generation that interprets systemic grammar as a computational representation. Terry 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 linguistic representations can be resolved. The study provides a detailed discussion of a substantial implementation involving a relatively large systemic grammar, and a formal model of the method. It represents a fundamental and productive contribution to the literature on text generation.
Terry Patten asserts that we are living at the center of a multidimensional and radical revolution. Recasting current problems as emergent opportunities, he points out humans' natural tendency to evol
This study explores an approach to text generation that interprets systemic grammar as a computational representation. Terry 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 linguistic representations can be resolved. The study provides a detailed discussion of a substantial implementation involving a relatively large systemic grammar, and a formal model of the method. It represents a fundamental and productive contribution to the literature on text generation.
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