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Evolving GATE to meet new challenges in language engineering

Published online by Cambridge University Press:  11 October 2004

KALINA BONTCHEVA ,
VALENTIN TABLAN ,
DIANA MAYNARD  and
HAMISH CUNNINGHAM
KALINA BONTCHEVA
Affiliation:
Department of Computer Science, University of Sheffield, Sheffield S1 4DP, UK e-mail: [email protected]@[email protected]@dcs.shef.ac.uk
VALENTIN TABLAN
Affiliation:
Department of Computer Science, University of Sheffield, Sheffield S1 4DP, UK e-mail: [email protected]@[email protected]@dcs.shef.ac.uk
DIANA MAYNARD
Affiliation:
Department of Computer Science, University of Sheffield, Sheffield S1 4DP, UK e-mail: [email protected]@[email protected]@dcs.shef.ac.uk
HAMISH CUNNINGHAM
Affiliation:
Department of Computer Science, University of Sheffield, Sheffield S1 4DP, UK e-mail: [email protected]@[email protected]@dcs.shef.ac.uk
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Abstract

In this paper we present recent work on GATE, a widely-used framework and graphical development environment for creating and deploying Language Engineering components and resources in a robust fashion. The GATE architecture has facilitated the development of a number of successful applications for various language processing tasks (such as Information Extraction, dialogue and summarisation), the building and annotation of corpora and the quantitative evaluations of LE applications. The focus of this paper is on recent developments in response to new challenges in Language Engineering: Semantic Web, integration with Information Retrieval and data mining, and the need for machine learning support.

Type
Papers
Information
Natural Language Engineering , Volume 10 , Issue 3-4 , September 2004 , pp. 349 - 373
Copyright
© 2004 Cambridge University Press

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Footnotes

Work on GATE has been supported by the Engineering and Physical Sciences Research Council (EPSRC) under grants GR/K25267 (Large-Scale Information Extraction), GR/M31699 (GATE 2), GR/N15764/01 (AKT), EMILLE, and by several smaller grants. We would like to thank the numerous people who have contributed to this work. Particularly Marin Dimitrov, Cristian Ursu, Oana Hamza, Borislav Popov, Atanas Kiryakov, Robert Gaizauskas, and Yorick Wilks for their contributions to GATE v2; and finally to Donia Scott and the three anonymous reviewers of this paper.