A Modality Lexicon and its use in Automatic Tagging

Kathryn Baker, Michael Bloodgood, Bonnie Dorr, Nathaniel W. Filardo, Lori Levin, Christine Piatko


Abstract
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.
Anthology ID:
L10-1309
Volume:
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)
Month:
May
Year:
2010
Address:
Valletta, Malta
Venue:
LREC
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Publisher:
European Language Resources Association (ELRA)
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URL:
http://www.lrec-conf.org/proceedings/lrec2010/pdf/446_Paper.pdf
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PDF:
http://www.lrec-conf.org/proceedings/lrec2010/pdf/446_Paper.pdf