I would appreciate it if anyone could point me to any recent (2004 or
later) results bearing on the usefulness of word sense disambiguation
(WSD) for end-user applications (such as machine translation or
question answering, and excluding WSD in support of NLP-internal tasks
such as parsing, semantic role labeling, learning selectional
preferences, etc.). For purposes of this query, WSD means
automatically assigning labels from a pre-existing sense inventory to
terms in input text (either with or without probabilities or
confidence values).
Carpuat and Wu's ACL-2005 paper is a nice example of the sort of thing
I'm looking for. Although a positive result would be even nicer. :-)
Please reply privately and I will summarize to the list if there's
interest.
Philip
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Philip Resnik, Associate Professor
Department of Linguistics and Institute for Advanced Computer Studies
1401 Marie Mount Hall UMIACS phone: (301) 405-6760
University of Maryland Linguistics phone: (301) 405-8903
College Park, MD 20742 USA Fax: (301) 314-2644 / (301) 405-7104
http://umiacs.umd.edu/~resnik E-mail: resnik_AT_umiacs.umd.edu
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