Augmenting English Adjective Senses with Supersenses

Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC 2014)

Abstract

We develop a supersense taxonomy for adjectives, based on that of GermaNet, and apply it to English adjectives in WordNet using human annotation and supervised classification. Results show that accuracy for automatic adjective type classification is high, but synsets are considerably more difficult to classify, even for trained human annotators. We release the manually annotated data, the classifier, and the induced supersense labeling of 12,304 WordNet adjective synsets.