Training a model which has such a huge number of classes is infeasible if the model does not factorize due to strong independence assumptions.
in order to be able to incorporate long-range dependencies in our models, we chose to adopt a re-ranking approach (Collins 2000), which selects from likely assignments generated by a model which makes stronger independence assumptions.