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<Paper uid="E91-1055">
  <Title>REFERENCES</Title>
  <Section position="4" start_page="0" end_page="0" type="ackno">
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3 COMPARISONS
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    <Paragraph position="0"> We are concerned here almost entirely with what has come to be known as the &amp;quot;tactical&amp;quot; component of language generation -- with how to realise some chosen message as NL text, rather than with how to decide what message we want realised. The two are not entirely separable, but we have little to say about &amp;quot;strategic&amp;quot; tasks such as deciding what properties should be used for characterising an item being referred to by an NP, which we expect the application program to deal with. The responsibility for deciding whether to pronominalise something, for instance, would be handed over to the application program by the NL system bluntly asking whether a description with the property qualif ier :pronoun was acceptable. We thus completely side-step the issues addressed by systems which plan what to say to produce specific effects in a hearer \[Appelt 1985\], which work out how organise multi-sentence texts in order to convey complex messages without disorienting the heater \[McKeown 1985\], or which invent effective descriptions for use in referring expressions /Dale 1988\]. These are all important tasks, but they are not what we are concerned with here.</Paragraph>
    <Paragraph position="1"> The most direct comparison is with \[Shieber et al. 1990\], where an approach to generating text from a given logical form is described. The algorithm described by Shieber and his colleagues takes a realisable A-calculus expression and uses their syntactic/semantic rules &amp;quot;backwards&amp;quot; to generate appropriate text. Their emphasis is on controlling the way these rules are applied, with rules satisfying certain rather stringent criteria being applied top-down and al\] other rules being used bottom-up. The algorithm looks effective, so long as (a) it is reasonable to assume that an application program can be relied on to produce realisable expressions in the representation language and (b) there are any rules which satisfy their criteria. We argued at some length above that the first of these conditions is unlikely to hold unless the application program knows a great deal about the syntactic/semantic rules which are going to be used. We also suspect that the way they control the top-down application of rules imposes unacceptable constraints on the way that semantic representations of wholes are composed out of semantic representations of parts. Certainly none of the rules we used in the system described in \[Ramsay 1990\] satisfy their criteria. We therefore believe that our approach, where the application decides whether the fragments of text proposed by the NL system are acceptable as they are proposed, is more flexible than any approach which depends on getting a reaiisable expression of the representation language from the application program and systematically translating it into a natural language using syntactic/semantic rules which were primarily designed for translating in the other direction.</Paragraph>
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