Here we propose a new approach to this set of issues: start with a model that explicitly entertains ambiguity, and gradually constrain it so that it eventually converges to an unambiguous tagger.
although the algorithm uses probabilistic assignments, of Gaussian-mixture type, the goal is the construction of hard assignments.