EZ.WordNet: Principles for Automatic Generation of a Coarse Grained WordNet

Rada Mihalcea and Dan I. Moldovan, Southern Methodist University, USA

In this paper, we propose several principles that enable the automatic transformation of WordNet into a coarser grained dictionary, without affecting its existing semantic relations. We derive a new version of WordNet leading to a reduction of 26% in the average polysemy of words, while introducing a small error rate of 2.1%, as measured on a sense tagged corpus.


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