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<Paper uid="C90-3053">
  <Title>The semantic representation of spatial configurations: a conceptual motivation for generation in Machine Translation</Title>
  <Section position="4" start_page="0" end_page="0" type="intro">
    <SectionTitle>
3. The process of schematization
</SectionTitle>
    <Paragraph position="0"> within a unification based environment Our implementation is done in the CAT2 system (cf. Sharp 1988), an extension of the MT prototype (cf. Arnold et al. 1986) formerly nsed in EUROTRA. Although differing primarily in the implementation, the basic translation philosophy has been preserved. The translation procedure is stratificational in that it is split up into the translation between several linguistically motivated levels, representing constituency, syntactic functions and semantic relations. In this paper we are only concerned with the semantic level, the Interface Structure (IS), which should contain the semantic information required for transfer, analysis and synthesis. For a more detailed description of tile current CAT2 system and the current 1S conception see Sharp 1988, Zelinsky-Wibbelt 1988 and 1989, and Steiner et at. 1988.</Paragraph>
    <Paragraph position="1"> Let us now relate the process of schematizatlon to generating a representation by stepwise rule application, where the rules include the instantiations of the schematlzatlon principles given in section 2 (&amp;quot;st&amp;quot; stands for semantic feature, &amp;quot;;&amp;quot; for disjunction, &amp;quot;pred&amp;quot; for predicate, &amp;quot;arg&amp;quot; for argument, and &amp;quot;rood&amp;quot; for orodifier). The language-specific semantic representation which unifies with tile correct preposition is generated in the respective target language component. We illustrate the translation of our example sentence &amp;quot;Die Kinder fahren irn Bus&amp;quot; into &amp;quot;The chitdretz are riding on the bus&amp;quot;. In order to keep the representation clear we give the rules in a very simplified version, containing only the information relevant in this context, namely tile information about the typicality, salience, and relevance of basic cognitive domains and domain-specific typical functions:  preserved during translation, is transferred. Rules (5) to (7) are lexieal rules denoting basic cognitive domains, whereas rule (4) denotes a typical function of a domain-specific entity. Both knowledge types are used in sentence rule (9), which effects that in sentences in which the verb inherently predicates a MOTION and has a PP-Modifier with an NP argument whose designated obiect - the landmark - typically functions as a LARGE VEtIICLE, TRANSpOIt.TABILITY is iastantiated as the salient property of the first NP argument of the verb, the trajector. What can then be instantiated is the idealization of the PP's NP-argument to a TWO-DIMENSIONAL SURPACE which is its salient part. Now the schematlzation type may be generated by rule (11). This rule effects that in a spatial configuration with a typically TIt/.,NSPOItTABLE trajector and a landmark which has a surface as its salient part, the relevant concept relating both trajector and landmark is that of SUPPORT, which unifies with the lexical rule (6) for the preposition on.</Paragraph>
    <Paragraph position="2"> The result of the generation process is represented in a simplified version in figure 3.</Paragraph>
    <Paragraph position="3"> predicate argtrnentl modifier  While in this example the discourse situation was given intrasententially by the action of riding, it will often only be given extrasententially. This opens an area for future research, which will also comprise interaction with a knowledge base.</Paragraph>
  </Section>
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