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<Paper uid="W01-0810">
  <Title>Linear order as higher-level decision: Information Structure in strategic and tactical generation</Title>
  <Section position="6" start_page="0" end_page="0" type="concl">
    <SectionTitle>
6 Summary and conclusions
</SectionTitle>
    <Paragraph position="0"> We have presented a flexible word ordering algorithm for natural language generation. The novel contribution consists in offering one way of implementing information structure as the major source of constraints on word order variation for languages with pragmatically-determined word order. Apart from that, the special feature of the word order algorithm proposed is that it can also be applied to languages with grammatically-determined word order. We have illustrated the application of the algorithm for Czech and English, Czech being a language in which word order is primarily pragmatically determined and English being a grammatically-determined word order language. We have thus provided evidence that the algorithm can flexibly be applied to 'free' word order languages as well as 'fixed' word order languages.</Paragraph>
    <Paragraph position="1"> From a linguistic theoretical point of view, the most important precondition for achieving this has been to take seriously the linguistic observation that in many languages information structure is the driving force for word order variation. For the modeling of information structure for strategic generation, we have drawn upon two well established linguistic frameworks, in both of which the discourse-linguistic and pragmatic constraints on grammatical realization are a focal interest, the Prague School and Systemic Functional Linguistics. From a technical point of view, we have based the implementation on the KPML system, integrating the proposed word order algorithm with existing multilingual grammatical resources and re-using KPML's mechanisms for word order realization as well as its systemic-functionally based notion of Theme. The algorithm is not KPML-specific, though, and could be applied in other frameworks as well, especially if they allow the combination of linearization constraints coming from different sources.</Paragraph>
  </Section>
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