When a complete tag lexicon is provided, our unsupervised model achieves an average accuracy of 95%, in comparison to 91% for an unsupervised monolingual Bayesian HMM and 97.4% for its supervised counterpart.
on average, the gap between unsupervised and supervised monolingual performance is cut by nearly two thirds.