In such models, the probability assigned to a tagged sequence of words x = t, w is the product of a sequence of local portions of the graphical model, one from each time slice.
the principal advantage of the dependency network approach is that advantageous bidirectional effects can be obtained without the extremely expensive global training required for CRFs.