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<Paper uid="P97-1025">
  <Title>Planning Reference Choices for Argumentative Texts</Title>
  <Section position="9" start_page="195" end_page="195" type="concl">
    <SectionTitle>
6 Conclusion
</SectionTitle>
    <Paragraph position="0"> This paper describes the way in which PROVERB refers to previouslyderived results while verbalizing machine-found proofs. By distinguishing between hierarchical planning and focus-guided navigation, PROVERB achieves a natural segmentation of context into an attentional hierarchy. Based on this segmentation, PRO VERB makes reference decisions according to a discourse theory adapted from Reichman for this special application.</Paragraph>
    <Paragraph position="1"> PROVERB works in a fully automatic way. The output texts are close to detailed proofs in text-books and are basically accepted by the community of automated reasoning. With the increasing size of proofs which PROVERB is getting as input, investigation is needed both for longer proofs as well as for more concise styles.</Paragraph>
    <Paragraph position="2"> Although developed for a specific application, we believe the main rationales behind of our system architecture are useful for natural language generation in general. Concerning segmentation of discourse, a natural segmentation can be easily achieved if we could distinguish between language generation activities affecting global structure of attention and those only moving the local focus. We believe a global attentional hierarchy plays a crucial role in choosing reference expressions beyond this particular domain of application. Furthermore, it turned out to be also important for other generation decisions, such as paragraph scoping and layout. Finally, the combination of hierarchical planning with local navigation needs more research as a topic in its own right. For many applications, these two techniques are a complementary pair.</Paragraph>
  </Section>
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