We outline a model of generation with revision, focusing on improving textual coherence. We argue that high quality text is more easily produced by iteratively revising and regenerating, as people do, rather than by using an architecturally more complex single pass generator. As a general area of study, the revision process presents interesting problems: Recognition of flaws in text requires a descriptive theory of what constitutes well written prose and a parser which can build a representation in those terms.Improving text requires associating flaws with strategies for improvement. The strategies, in turn, need to know what adjustments to the decisions made during the initial generation will produce appropriate modifications to the text. We compare our treatment of revision with those of Mann and Moore (1981), Gabriel (1984), andMann (1983).
This paper presents an analysis of a family of particular English constructions, all of which roughly express "purpose". In particular we look at the purpose clause, rationale .clause, and infinitival relative clause. We (1) show that couching the analysis in a computational framework, specifically generation, provides a more satisfying account than analyses based strictly on descriptive linguistics, (2) describe an implementation of our analysis in the natural language generation system MUMBLE-86, and (3) discuss how our architecture improves upon the techniques used by other generation systems for handling these and other adjunct constructions.
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