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    Semantic Representation of Natural Language

    AvMichael Levison,Greg Lessard

    E-bok
    Engelska, 2012

    Del i serien Bloomsbury Studies in Theoretical Linguistics

    606 kr

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    E-bok

    606 kr

    Inbunden

    2 431 kr

    Häftad

    563 kr

    Beskrivning

    This volume contains a detailed, precise and clear semantic formalism designed to allow non-programmers such as linguists and literary specialists to represent elements of meaning which they must deal with in their research and teaching. At the same time, by its basis in a functional programming paradigm, it retains sufficient formal precision to support computational implementation.The formalism is designed to represent meaning as found at a variety of levels, including basic semantic units and relations, word meaning, sentence-level phenomena, and text-level meaning. By drawing on fundamental principles of program design, the proposed formalism is both easy to read and modify yet sufficiently powerful to allow for the representation of complex semantic phenomena.In this monograph, the authors introduce the formalism and show its basic structure, apply it to the analysis of the semantics of a variety of linguistic phenomena in both English and French, and use it to represent the semantics of a variety of texts ranging from single sentences, to textual excepts, to a full story.

    Produktinformation

    • Utgivningsdatum:2012-12-20
    • Språk:Engelska
    • Antal sidor:352
    • Filformat:EPUB
    • Kopieringsskydd:LCP
    • ISBN:9781441190734
    • Förlag:Bloomsbury Publishing PLC (Digital)
    • Serie:Bloomsbury Studies in Theoretical Linguistics

    Utforska kategorier

    • Språkvetenskap och lingvistik inom Språk och ordböcker

    Mer om författaren

    Michael Levison is a Professor Emeritus in the School of Computing at Queen's University,Canada.Greg Lessard is a Professor in the Department of French Studies at Queen's University, Canada.Craig Thomas earned his PhD from the School of Computing at Queen's University, Canada, in2010 under the supervision of Michael Levison and Greg Lessard.Matthew Donald earned his MSc from the School of Computing at Queen's University, Canada, in2006 under the direction of Michael Levison and Greg Lessard.

    Recensioner i media

    At last a book on natural language semantics that tackles semantics all the way up to texts of considerable length and fictional statements. The proposed formalism brings together well tried solutions for specific linguistic phenomena with a structural approach based on programming languages that makes it user friendly and gives it tremendous expressive power. A very useful contribution for natural language generation and the representation of narrative. -- Pablo Gervas, Associate Professor, Universidad Complutense de Madrid, Spain Semantic Representations of Natural Language provides a highly suggestive survey of the multiple relationships between semantic analysis and computational formalization of natural language and narratives, offering a vivid, nearly kaleidoscopic, theoretically comprehensive and strongly argued synthesis of a long lasting team approach. Even literature researchers concerned with the digital analysis of textuality will read this monograph with the greatest interest. -- Jean-Pierre Dubost, Emeritus Professor, Universite Blaise Pascal, France Genuine interdisciplinary research between linguistics, literary studies and computational approaches is rare. The research detailed here is an example of such interdisciplinary collaboration at its best. Technical, but enjoyable, this is a book to be read and thought about as it opens many new vistas. -- Geoffrey Williams, Professor, Universite De Bretagne-Sud, France

    Innehållsförteckning

    • List of FiguresList of TablesPrefaceTypographical Conventions1. Introduction2. Basic Concepts3. Previous Approaches4. Semantic Expressions: Introduction5. Formal Issues6. Semantic Expressions: Basic Features7. Advanced Features8. Applications: Capture9. Three Little Pigs10. Applications CreationBibliographyIndex
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