Our work is grounded in the notion that by trying to explain the POS bigram counts in a target corpus, we can discover a stochastic realization policy for the target language, which correctly "translates" the source trees into appropriate target trees.
8 This pruning heuristic retains 36.1% of the trees (averaging over the 20 development treebanks ( §5.1)) for training, and 66.6% for actual realization.