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<Paper uid="E85-1037">
  <Title>A PROBLEM SOLVING APPROACH TO GENERATING TEXT FROM SYSTEMIC GRAMMARS*</Title>
  <Section position="9" start_page="255" end_page="256" type="concl">
    <SectionTitle>
CONCLUSION
</SectionTitle>
    <Paragraph position="0"> This paper has described a new approach to generating text from systemic grammars. State-of-the-art AI problem solving techniques are applied directly to an unadulterated systemic grammar. We have seen how this approach is made possible by a special relationship between systemic linguistics and AI problem solving. A semantic stratum, consisting of a large knowledge base relating different 'registers' to grammatical features, preselects some features from the grammatical level. The large number of features which are not preselected are inferred efficiently by goal-directed backward chaining and forward chaining.</Paragraph>
    <Paragraph position="1"> This approach has the advantage of being able to combine an established linguistic formalism with powerful AI methods. It also has the advantage of simplicity resulting from the application of these same methods throughout the generation process.</Paragraph>
    <Paragraph position="2"> This approach has been applied successfully to a large grammatical stratum. Of course it will not have been tested properly until a substantial semantic stratum is developed.</Paragraph>
    <Paragraph position="3"> In conclusion, although there are still many unresolved linguistic matters in systemic text generation, we hope this approach has moved toward solving the computational problems involved.</Paragraph>
    <Paragraph position="4"> * Following an example from \[Hasling et al., 1984).</Paragraph>
  </Section>
class="xml-element"></Paper>