Multiplicity and word sense: evaluating and learning from multiply labeled word sense annotations.

Supervised machine learning methods to model word sense often rely on human labelers to provide a single, ground truth label for each word in its context. We examine issues in establishing ground truth word sense labels using a fine-grained sense inventory from WordNet. Our data consist of a sentenc...

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Bibliographic Details

Published in:	Language Resources & Evaluation Vol. 46; no. 2; pp. 219 - 253
Main Authors:	Passonneau, Rebecca, Bhardwaj, Vikas, Salleb-Aouissi, Ansaf, Ide, Nancy
Format:	Article
Published:	Springer Nature Jun2012
Subjects:	Annotations Machine learning Senses Corpora Polysemy Sentences (Grammar) Vocabulary
Online Access:	View this record in EBSCOhost