, where s tree p is the hidden state of rule RNN that generated the CFG rule above the current terminal; w t 1 is the embedding of the word generated at time step t 1; and c t 1 is the attention context computed at the previous word RNN time step t 1.   , where W varies depending on whether a rule or a subword unit is needed.
it is an open question of what specific linguistic formalism, if any, is the best structural representation for NMT.