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<Paper uid="P98-2173">
  <Title>Multilingual authoring using feedback texts</Title>
  <Section position="1" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> There are obvious reasons for trying to automate the production of multilingual documentation, especially for routine subject-matter in restricted domains (e.g. technical instructions).</Paragraph>
    <Paragraph position="1"> Two approaches have been adopted: Machine Translation (MT) of a source text, and Multi-lingual Natural Language Generation (M-NLG) from a knowledge base. For MT, information extraction is a major difficulty, since the meaning must be derived by analysis of the source text; M-NLG avoids this difficulty but seems at first sight to require an expensive phase of knowledge engineering in order to encode the meaning. We introduce here a new technique which employs M-NLG during the phase of knowledge editing. A 'feedback text', generated from a possibly incomplete knowledge base, describes in natural language the knowledge encoded so far, and the options for extending it.</Paragraph>
    <Paragraph position="2"> This method allows anyone speaking one of the supported languages to produce texts in all of them, requiring from the author only expertise in the subject-matter, not expertise in knowledge engineering.</Paragraph>
  </Section>
class="xml-element"></Paper>