Models and Training for Unsupervised Preposition Sense Disambiguation
Dirk Hovy, Ashish Vaswani, Stephen Tratz, David Chiang, Eduard H. Hovy · 2011
We present a preliminary study on unsupervised preposition sense disambiguation (PSD), comparing different models and training techniques (EM, MAP-EM with L0 norm, Bayesian inference using Gibbs sampling). To our knowledge, this is the first attempt at unsupervised preposition sense disambiguation. Our best accuracy reaches 56%, a significant improvement (at p <.001) of 16 % over the most-frequent-sense baseline. 1