Metaphor. Tony Veale

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Metaphor - Tony Veale Synthesis Lectures on Human Language Technologies

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Kübler, Ryan McDonald, and Joakim Nivre

      2009

      Statistical Language Models for Information Retrieval

      ChengXiang Zhai

      2008

      Copyright © 2016 by Morgan & Claypool

      All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means—electronic, mechanical, photocopy, recording, or any other except for brief quotations in printed reviews, without the prior permission of the publisher.

      Metaphor: A Computational Perspective

      Tony Veale, Ekaterina Shutova, and Beata Beigman Klebanov

       www.morganclaypool.com

      ISBN: 9781627058506 paperback

      ISBN: 9781627058513 ebook

      DOI 10.2200/S00694ED1V01Y201601HLT031

      A Publication in the Morgan & Claypool Publishers series

       SYNTHESIS LECTURES ON HUMAN LANGUAGE TECHNOLOGIES

      Lecture #31

      Series Editor: Graeme Hirst, University of Toronto

      Series ISSN

      Print 1947-4040 Electronic 1947-4059

       Metaphor

       A Computational Perspective

      Tony Veale

      University College Dublin

      Ekaterina Shutova

      University of Cambridge

      Beata Beigman Klebanov

      Educational Testing Service

       SYNTHESIS LECTURES ON HUMAN LANGUAGE TECHNOLOGIES #31

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       ABSTRACT

      The literary imagination may take flight on the wings of metaphor, but hard-headed scientists are just as likely as doe-eyed poets to reach for a metaphor when the descriptive need arises. Metaphor is a pervasive aspect of every genre of text and every register of speech, and is as useful for describing the inner workings of a “black hole” (itself a metaphor) as it is the affairs of the human heart. The ubiquity of metaphor in natural language thus poses a significant challenge for Natural Language Processing (NLP) systems and their builders, who cannot afford to wait until the problems of literal language have been solved before turning their attention to figurative phenomena. This book offers a comprehensive approach to the computational treatment of metaphor and its figurative brethren—including simile, analogy, and conceptual blending—that does not shy away from their important cognitive and philosophical dimensions. Veale, Shutova, and Beigman Klebanov approach metaphor from multiple computational perspectives, providing coverage of both symbolic and statistical approaches to interpretation and paraphrase generation, while also considering key contributions from philosophy on what constitutes the “meaning” of a metaphor. This book also surveys available metaphor corpora and discusses protocols for metaphor annotation. Any reader with an interest in metaphor, from beginning researchers to seasoned scholars, will find this book to be an invaluable guide to what is a fascinating linguistic phenomenon.

       KEYWORDS

      metaphor, simile, analogy, blending, figurative language processing

       Contents

       Preface

       1 Introducing Metaphor

       2 Computational Approaches to Metaphor: Theoretical Foundations

       2.1 The What, Why and How of Metaphor

       2.2 The “Meaning” of Metaphor

       2.3 Paraphrasing Metaphor

       2.4 Metaphor and Simile

       2.5 Metaphor and Analogy

       2.5.1 Domain Representations in Metaphor and Analogy

       2.6 Conceptual Metaphor Theory

       2.7 Conceptual Integration and Blending

       2.8 An Integrated Perspective

       3 Artificial Intelligence and Metaphor

       3.1 Corrective Approaches: Metaphor Diagnosis and Repair

       3.2 Analogical Approaches: Mapping Meanings between Domains

       3.3 Schematic Approaches: Families of Metaphor

       3.4 Common Themes and Future Prospects

       4 Metaphor Annotation

       4.1 Metaphor Identification in Corpus Linguistics

       4.2 The MIP Overall

       4.3 Specifications of Auxiliary Concepts

       4.3.1 Sense Inventories

       4.3.2 Criterion for Sense Distinctiveness

       4.3.3 Lexical Unit

       4.4 The MIP in Languages other than English

       4.5 Annotated Datasets

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