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<Paper uid="P92-1033">
  <Title>A PARAMETERIZED APPROACH TO INTEGRATING ASPECT WITH LEXICAL-SEMANTICS FOR MACHINE TRANSLATION</Title>
  <Section position="3" start_page="0" end_page="257" type="intro">
    <SectionTitle>
INTRODUCTION
</SectionTitle>
    <Paragraph position="0"> This paper discusses how the two-level knowledge representation model for machine translation presented by Dorr (1991) integrates aspectual information with lexical-semantic information by means of parameterization. The parameter-based approach borrows certain ideas from previous work such as the lexical-semantic model of Jackendoff (1983, 1990) and models of aspectual representation including Bach (1986), Comrie (1976), Dowty (1979), Mourelatos (1981), Passonneau (1988), Pustejovsky (1988, 1989, 1991), and Vendler (1967). However, unlike previous work, the current approach examines aspectual considerations within the context of machine translation. More recently, Bennett *This paper describes research done in the Institute for Advanced Computer Studies at the University of Maryland.</Paragraph>
    <Paragraph position="1"> A special thanks goes to Terry Gaasterland and Ki Lee for helping to close the gap between properties of aspectual information and properties of lexical-semantic structure. In addition, useful guidance and commentary during this research were provided by Bruce Dawson, Michael Herweg,  (1) Syntactic: (a) Null Subject divergence: E: I have seen Mary 4. S: He vlsto a Marls (Have seen (to) Mary) (b) Constituent Order divergence, E: I have seen Mary 4. G: Ich habe Marie gesehen (I have Mar~&amp;quot; seen) (2) Lexicel-Semantic: (a) Thematic divergence: E: I like Mary 4. $: Marls me gusts a mf (Mary pleases me) (b) Structural divergence: E: John entered the house 4. S: Juan entr6 en la cas&amp; (John entered in the house) (c) Cat esorlal divergence: E: Yo ten~o hambre 4* S: Ich habe Hun~er (I have hun~er) (3) Aepectuah  et el. (1990) have examined aspect and verb semantics within the context of machine translation in the spirit of Moens and Steedman (1988). This paper borrows from, and extends, these ideas by demonstrating how this theoretical framework might be adapted for cross-linguistic applicability. The framework has been tested within the context of an interlingual machine translation system and is currently being used as the basis for extraction of aspectual information from corpora. The integration of aspect with lexical-semantics is especially critical in machine translation because of the lexical selection and aspectual realization processes that operate during the production of the target-language sentence: there are often a large number of lexical and aspectual possibilities to choose from in the production of a sentence from a lexical semantic representation. Aspectual information from the source-language sentence constrains the choice of target-language terms. In turn, the target-language terms limit the possibilities for generation of aspect. Thus, there is a two-way communication channel between the two processes.</Paragraph>
    <Paragraph position="2"> Figure 1 shows some of the types of parametric diver- null We will focus primarily on the third type, aspectual distinctions, and show how these may be discovered through the extraction of information in a monolingual corpus. We adopt the viewpoint that the algorithms for extraction of syntactic, lexical-semantic, and aspectual information must be well-grounded in linguistic theory. Once the information is extracted, it may then be used as the basis of parameterized machine translation. Note that we reject the commonly held assumption that the use of corpora necessarily suggests that statistical or example-based techniques be used as the basis for a machine translation system.</Paragraph>
    <Paragraph position="3"> The following section discusses how the two levels of knowledge, aspectual and lexical-semantic, are used in an interlingual model of machine translation. We then describe how this information may be parameterized. Finally, we discuss how the automatic acquisition of new lexical entries from corpora is achieved within this framework. null</Paragraph>
  </Section>
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