Concretely, if we find that the current classifier already has acceptably strong confidence on its classification results for all remained unlabeled data, we assume the current training data is sufficient to train the classifier with maximum effectiveness.
in practice, for WSD, the costs of various senses of a disambiguated word are unequal and unknown, and they are difficult to evaluate in the process of learning.