Therefore, we adopt a "distillation approach", where we train a supervised model over abstract examples to mimic the predictions of an unsupervised model that has access to the full lexicalized examples.
we use a standard unsupervised word aligner (Dyer et al., 2013), which takes all lexicalized examples {( i=1 in all D domains and produces an Alignment matrix A * for every example, where A * ij = 1 iff token i in the logical form is aligned to token j in the utterance.