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Titlebook: Lexical Semantics and Knowledge Representation in Multilingual Text Generation; Manfred Stede Book 1999 Springer Science+Business Media Ne

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書目名稱Lexical Semantics and Knowledge Representation in Multilingual Text Generation
編輯Manfred Stede
視頻videohttp://file.papertrans.cn/586/585439/585439.mp4
叢書名稱The Springer International Series in Engineering and Computer Science
圖書封面Titlebook: Lexical Semantics and Knowledge Representation in Multilingual Text Generation; Manfred Stede Book 1999 Springer Science+Business Media Ne
描述In knowledge-based natural language generation, issues offormal knowledge representation meet with the linguistic problems ofchoosing the most appropriate verbalization in a particular situationof utterance. .Lexical Semantics and Knowledge Representation in..Multilingual Text Generation. presents a new approach tosystematically linking the realms of lexical semantics and knowledgerepresented in a description logic. For language generation from suchabstract representations, lexicalization is taken as the central step:when choosing words that cover the various parts of the contentrepresentation, the principal decisions on conveying the intendedmeaning are made. A preference mechanism is used to construct theutterance that is best tailored to parameters representing thecontext. ..Lexical Semantics and Knowledge Representation in MultilingualText. .Generation. develops the means for systematicallyderiving a set of paraphrases from the same underlying representationwith the emphasis on events and verb meaning. Furthermore, the samemapping mechanism is used to achieve multilingual generation: Englishand German output are produced in parallel, on the basis of anadequate division between
出版日期Book 1999
關(guān)鍵詞Extension; artificial intelligence; cognitive science; description logic; intelligence; knowledge; knowled
版次1
doihttps://doi.org/10.1007/978-1-4615-5179-9
isbn_softcover978-1-4613-7359-9
isbn_ebook978-1-4615-5179-9Series ISSN 0893-3405
issn_series 0893-3405
copyrightSpringer Science+Business Media New York 1999
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Modelling the Domain,e set out to achieve, the decisions for domain modelling need to be made carefully. Thus, Chapter 4 develops the domain model for the generator: the taxonomy of concepts and relations that, in later chapters, the generation system will be based on.
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Levels of Representation: Sitspec and Semspec,and trying to map these structures directly to linguistic output would not be a promising endeavor. Very many decisions need to be made, and, particularly in a multilingual environment, a lot of work would be duplicated if language-specific modules were in charge of the complete mapping, because man
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Representing the Meaning of Words,link the lexemes to the representation system in which the input to the generator is specified. When input structures are relatively fine-grained (as in our Sit-Specs), lexico-semantic specifications need to be complex, too, so that the two can be matched. The gain, of course, is possible variety in
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From Sentences to Text,r producing paragraph-size text. In this chapter, we show some possibilities for extending the MOOSE sentence generation framework “upward” to the production of paragraphs. Section 10.1 discusses some general issues of text planning and representation, and Section 10.2 sketches some of the steps nec
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