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Rethinking Translation Unit Size: an Empirical Study of an English-Japanese Newswire Corpus

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CORE Metadata, citation and similar papers at core.ac.uk Provided by University of Birmingham Research Archive, E-theses Repository RETHINKING TRANSLATION UNIT SIZE: AN EMPIRICAL STUDY OF AN ENGLISH-JAPANESE NEWSWIRE CORPUS BY FUMIKO KONDO A THESIS SUBMITTED TO THE UNIVERSITY OF BIRMINGHAM FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF ENGLISH COLLEGE OF ARTS AND LAW THE UNIVERSITY OF BIRMINGHAM NOVEMBER 2009 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. ABSTRACT The translation unit has been regarded as an elusive notion in linguistics. The literature shows that there seems to be little agreement regarding, in particular, their identification and size. This study attempts to rethink these two central issues of translation units with the help of a parallel corpus: the ARC (the Alignment of Reuters Corpora), an English-Japanese newswire corpus. The main achievements of this study are: the identification of five variables associated with translation unit size; the establishment of an unbiased, reproducible identification method; and, the demonstration that translation pairs (i.e. translation units and their equivalents) are ideal for contrastive analysis. The identification method, ‘the one-equivalent principle’, established in this thesis is justified linguistically by a thorough, systematic review of the relevant literature, and empirically using nine case studies. The target words of the case studies were the most frequent content words in the ARC: market; government; year; economic; new; foreign; said; told; and, expected. The examination of translation unit size, as well as non-translation units and translation pairs, shows that parallel corpora, and the one-equivalent principle, are powerful tools for understanding the nature of translation units. For Shoji, Akemi, and Oliver ACKNOWLEDGEMENTS I am deeply grateful to the academic staff and my colleagues at the University of Birmingham. Special thanks are due to my supervisor, Professor Wolfgang Teubert. His profound knowledge and encouraging comments have always stimulated me; his warm heart has eased me when it was needed. Also, I am indebted to my academic advisers, Professor Susan Hunston and Professor Michael Toolan, for showing me the direction when I was struggling at an early stage of my PhD journey. Dr Pernilla Danielsson is another person to who I owe a word of special thanks for her computational help and sympathetic advice. I owe a debt of gratitude to some linguists outside of Birmingham as well. First, I would like to express my sincere thanks to the National Institute of Standards and Technology (NIST) in Japan. They gave me permission to use and quote from their English-Japanese parallel corpus for this thesis: the Alignment of Reuters Corpora (ARC). Second, I am very fortunate to have had opportunities to exchange linguistic opinions with Professor Silvia Bernardini, Professor Kaoru Akasu, and Dr Dorothy Kenny, at various conferences and workshops. Their inspiring comments have helped to shape this PhD project. Also, Professor Michael Barlow, Professor Mike Scott, and Professor Paul Rayson offered their help and time when I had some questions regarding their software tools: ParaConc, WordSmith, Wmatrix, respectively. Third, I would like to express my gratitude to the School of Humanities and the Rotary Foundation for their financial supports. Without their scholarships, I could not have embarked on, or completed, my PhD career. I also would like to thank my parents, Shoji and Akemi, for their ever-present love and support. Without their patience and understanding, I could not have accomplished this academic challenge. Lastly, but not the least, my gratitude goes to my husband, Oliver, for his mental and intellectual support throughout the whole journey of my PhD, and for his tireless and precise proof-reading. In particular, his encouragement was irreplaceable when I felt I would never finish this thesis. TABLE OF CONTENTS 1. Introduction ..........................................................................................1 1.1. Organisation of the thesis ................................................................................. 3 1.2. Terms ................................................................................................................ 5 1.3. The representation of Japanese data ................................................................. 6 2. Translation unit size ...........................................................................10 2.1. Disagreement in the literature..........................................................................11 2.2. Cognitive unit ................................................................................................. 13 2.2.1. Definitions .................................................................................................. 13 2.2.2. Identifications ............................................................................................. 14 2.3. Lexical unit..................................................................................................... 18 2.3.1. Definitions .................................................................................................. 18 2.3.2. Identifications ............................................................................................. 22 2.4. What causes the disagreement? ...................................................................... 25 2.4.1. The dichotomy between the definitions ..................................................... 25 2.4.2. Language pairs............................................................................................ 30 2.4.3. Text types.................................................................................................... 36 2.4.4. Translators .................................................................................................. 38 2.4.5. Implications ................................................................................................ 40 2.5. Conclusion...................................................................................................... 44 3. Data and methodology .......................................................................45 3.1. Research question........................................................................................... 45 3.2. Corpus data..................................................................................................... 47 3.2.1. Advantages ................................................................................................. 50 3.2.2. Limitations.................................................................................................. 53 3.3. Existing methods ............................................................................................ 56 3.3.1. Degree of cohesion ..................................................................................... 56 3.3.2. No leftover principle................................................................................... 60 3.3.3. Monosemous principle ............................................................................... 63 3.3.4. Units of meaning ........................................................................................ 67 3.3.5. Summary..................................................................................................... 71 3.4. An alternative method .................................................................................... 72 3.4.1. One-equivalent principle ............................................................................ 75 3.4.2. Method........................................................................................................ 75 3.4.3. Noise examples........................................................................................... 78 3.4.4. Preliminary work ........................................................................................ 80 3.4.5. Target words ............................................................................................... 83 3.4.6. Analytical tools........................................................................................... 89 3.4.7. Advantages ................................................................................................. 94 3.4.8. Limitations.................................................................................................. 96 3.4.9. Summary..................................................................................................... 98 3.5. Hypotheses ..................................................................................................... 99 3.6. Conclusion.................................................................................................... 103 4. Analyses of nouns .............................................................................104 4.1. Translation units ..........................................................................................
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