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<Paper uid="P87-1004">
  <Title>JETR: A ROBUST MACHINE TRANSLATION SYSTEM</Title>
  <Section position="2" start_page="0" end_page="0" type="intro">
    <SectionTitle>
INTRODUCTION
</SectionTitle>
    <Paragraph position="0"> Recently there has been a revitalized interest in machine translation as both a practical engineering problem and a tool to test various Artificial Intelligence (AI) theories. As a result of increased international communication, there exists today a massive Japanese effort in machine translation.</Paragraph>
    <Paragraph position="1"> However, systems ready for commercialization are still concentrating on syntactic information and are unable to translate syntactically obscure but meaningful sentences. Moreover, many of these systems do not perform context analysis and thus cannot fill ellipses or resolve pronoun references. Knowledge-based systems, on the other hand, tend to discard the syntax of the source text and thus are unable to preserve the syntactic style of the source text. Moreover, these systems concentrate on understanding and thus do not preserve the semantic content of the source text.</Paragraph>
    <Paragraph position="2"> An expectation-based approach to &amp;quot;Japanese-to-English machine translation is presented. The approach is demonstrated by the JETR system which is designed to translate recipes and instruction booklets.</Paragraph>
    <Paragraph position="3"> Unlike other Japanese-to-English translation systems, which rely on the presence of particles and main verbs in the source text (AAT 1984, Ibuki 1983, Nitta 1982, tThe author is now located at:  Saino 1983, Shimazu 1983), JETR is designed to translate ungrammatical and abbreviated sentences using semantic and contextual information. Unlike other knowledge-based translation systems (Cullingford 1976, Ishizaki 1983, Schank 1982, Yang 1981), JETR does not view machine translation as a paraphrasing problem. JETR attempts to achieve semantic, pragmatic, structural and lexical invariance which (Carbonell 1981) gives as multiple dimensions of quality in the translation process.</Paragraph>
    <Paragraph position="4"> Sends phrases, wood d~sses and phrase roles \[Analyzer\[  the particle-driven analyzer, the generator, and the context analyzer as shown in Figure 1. The three components interact with one another to preserve information contained in grammatical as well as ungrammatical texts. The overview of each component is presented below. This paper focuses on the particle-driven analyzer.</Paragraph>
  </Section>
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