A Modality Lexicon and its use in Automatic Tagging
Kathryn Baker, Michael Bloodgood, Bonnie J. Dorr, Nathaniel W. Filardo, Lori Levin, and Christine Piatko. 2010. A modality lexicon and its use in automatic tagging. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), pages 1402-1407, Valletta, Malta, May. European Language Resources Association.
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This paper describes our resource-building results for an eight-week JHU Human Language Technology Center of Excellence Summer Camp for Applied Language Exploration (SCALE-2009) on Semantically-Informed Machine Translation. Specifically, we describe the construction of a modality annotation scheme, a modality lexicon, and two automated modality taggers that were built using the lexicon and annotation scheme. Our annotation scheme is based on identifying three components of modality: a trigger, a target and a holder. We describe how our modality lexicon was produced semi-automatically, expanding from an initial hand-selected list of modality trigger words and phrases. The resulting expanded modality lexicon is being made publicly available. We demonstrate that one tagger—a structure-based tagger—results in precision around 86% (depending on genre) for tagging of a standard LDC data set. In a machine translation application, using the structure-based tagger to annotate English modalities on an English-Urdu training corpus improved the translation quality score for Urdu by 0.3 Bleu points in the face of sparse training data.
RightsPublished with the permission of ELRA. This paper was published within the proceedings of the LREC 2010 Conference. © 1998-2012 ELRA - European Language Resources Association. All rights reserved.
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