Trends in Parsing Technology Dependency Parsing, Domain Adaptation,
Parsing technology is a central area of research in the automatic processing of human language. It is concerned with the decomposition of complex structures into their constituent parts, in particular with the methods, the tools and the software to parse
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Text, Speech and Language Technology VOLUME 43
Series Editors Nancy Ide, Vassar College, New York Jean Véronis, Université de Provence and CNRS, France Editorial Board Harald Baayen, Max Planck Institute for Psycholinguistics, The Netherlands Kenneth W. Church, Microsoft Research Labs, Redmond WA, USA Judith Klavans, Columbia University, New York, USA David T. Barnard, University of Regina, Canada Dan Tufis, Romanian Academy of Sciences, Romania Joaquim Llisterri, Universitat Autonoma de Barcelona, Spain Stig Johansson, University of Oslo, Norway Joseph Mariani, LIMSI-CNRS, France
For further volumes: http://www.springer.com/series/6636
Trends in Parsing Technology Dependency Parsing, Domain Adaptation, and Deep Parsing Edited by
Harry Bunt Tilburg University, The Netherlands
Paola Merlo University of Geneva, Switzerland
and
Joakim Nivre Växjö University and Uppsala University, Sweden
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Editors Harry Bunt Tilburg University Tilburg Center for Cognition and Communication (TiCC) and Dept. of Communication and Information Sciences Warandelaan 2 5000 LE Tilburg Netherlands [email protected]
Paola Merlo Université de Genève Dépt. Linguistique rue de Candolle 2 1211 Genève Switzerland [email protected]
Joakim Nivre Växjö University Uppsala University Pimpstensvägen 16 752 67 Uppsala Sweden [email protected]
ISSN 1386-291X ISBN 978-90-481-9351-6 e-ISBN 978-90-481-9352-3 DOI 10.1007/978-90-481-9352-3 Springer Dordrecht Heidelberg London New York Library of Congress Control Number: 2010936679 c Springer Science+Business Media B.V. 2010 No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Contents
1 Current Trends in Parsing Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . Paola Merlo, Harry Bunt, and Joakim Nivre
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2 Single Malt or Blended? A Study in Multilingual Parser Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Johan Hall, Jens Nilsson, and Joakim Nivre 3 A Latent Variable Model for Generative Dependency Parsing . . . . . . . 35 Ivan Titov and James Henderson 4 Dependency Parsing and Domain Adaptation with Data-Driven LR Models and Parser Ensembles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Kenji Sagae and Jun-ichi Tsujii 5 Dependency Parsing Using Global Features . . . . . . . . . . . . . . . . . . . . . . . 69 Tetsuji Nakagawa 6 Dependency Parsing with Second-Order Feature Maps and Annotated Semantic Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Massimiliano Ciaramita and Giuseppe Attardi 7 Strictly Lexicalised
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