Uncovering textual meanings: a case study involving systemic-functional resources for the generation of Japanese texts

  • John A. Bateman
Part of the The Kluwer International Series in Engineering and Computer Science book series (SECS, volume 119)


A functional grammar of the systemic-functional variety decomposes the generation process in terms of sets of interrelated, functionally motivated grammatical alternatives. When such a grammar is used for generation, it has distinct informational needs: that is, if its supporting environment does not contain the information that the grammar requires in order to motivate the grammatical alternatives it offers, generation cannot proceed. The chooser and inquiry framework designed for the PENMAN system further decomposes grammatical alternatives into finer-grained semantic alternatives. These latter place specific constraints on the kinds of information that a generation system, and any underlying theory of semantics, must support and so can be used for determining what kinds of information are necessary. Significantly, the informational needs of a systemic-functional grammar are not restricted to ‘propositional content’-related areas: textual and interpersonal areas are also entailed. The methodology of uncovering semantic distinctions based on the informational needs of a grammar should then be applicable in these areas also. In this paper, I investigate the area of textual meanings as required by a small, experimental systemic-functional grammar of Japanese. I conclude that the methodology is, indeed, appropriate for uncovering textual meanings and needs to be pursued on a larger scale.


Text Base Computational Linguistics Text Generation Natural Language Generation Grammatical Relation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer Science+Business Media New York 1991

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  • John A. Bateman

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