Semantically rich human-aided machine annotation

Authors:
Marjorie McShane;Sergei Nirenburg;Stephen Beale;Thomas O'Hara
Affiliations:
University of Maryland, Baltimore, Maryland;University of Maryland, Baltimore, Maryland;University of Maryland, Baltimore, Maryland;University of Maryland, Baltimore, Maryland
Venue:
CorpusAnno '05 Proceedings of the Workshop on Frontiers in Corpus Annotations II: Pie in the Sky
Year:
2005

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Abstract

This paper describes a semantically rich, human-aided machine annotation system created within the Ontological Semantics (OntoSem) environment using the DEKADE toolset. In contrast to mainstream annotation efforts, this method of annotation provides more information at a lower cost and, for the most part, shifts the maintenance of consistency to the system itself. In addition, each tagging effort not only produces knowledge resources for that corpus, but also leads to improvements in the knowledge environment that will better support subsequent tagging efforts.