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<Paper uid="W00-1216">
  <Title>Text Meaning Representation for Chinese</Title>
  <Section position="9" start_page="113" end_page="113" type="concl">
    <SectionTitle>
6 Discussion
</SectionTitle>
    <Paragraph position="0"> A knowledge-based machine translation can be viewed as extracting and representing the meaning of a text and generating a text in target language based on the meaning presented. Thus, text meaning representation plays the key role in an interlingual approach to machine translation. The approach described in this article enables integrating linguistic knowledge of source languages with general world knowledge to reach high quality translation. It is because TMR represents meaning deeper and broader than what the context presents. For example, in the context ~. ~9~ provide service, the linguistic information indicates syntactic-semantic dependency as SUBJ (human) -V(service-event)-OBJ(event). In an ontology, the SERVICE-EVENT concept frame contains information about AGENT and THEME as well as BENEFI-CIARY, ACCOMPANIEtL INSTRUMENT, LOCA-TION, etc. which extends the meaning of the given text ~ ~ to lEA. :~ ~ ~ i~,A.</Paragraph>
    <Paragraph position="1"> ~. ~ ~ Someone provides service to someone else at some place. If the extended information is not explicitly presented in the text, the default value provides the assumption based on the world knowledge. In machine translation, it enables the generation of high quality text, especially in the case where the syntax in source language is different from that in target language or in the case where ellipsis is allowed in one language such as He plays Bach in English, but is not allowed in other language such as in Chinese, where one must say ~ ~ ~ fi.\] ~ ~ He plays Bach's work.</Paragraph>
    <Paragraph position="2"> With the rapid development of internet, information retrieval plays the key role in search engin. The extended information about the world knowledge allows to retrieve relevant data through the ontology that is implicitly specified in the query. As result, more broad and deep information can be extracted. It is extremely valuable to the development of next generation of internet search engin. All in all, using ontology strengthens all NLP systems.</Paragraph>
  </Section>
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