By contrast, in the CL learning regime, the incremental loss is computed as − log p (y t ), where p (y t ) is normalized only over the values of y t that are possible continuations once the grammar-induced constraints are taken into account, ignoring whatever weights the RNN predictor may (wrongly) believe should be put on impossible continuations.
when the grammar is known (in fact, as soon as the CFG core of the grammar is known), two properties of the DS hold (we omit the easy algorithms underlying these properties; they involve using a prefix of the DS for constructing a partial derivation tree in a top-down fashion): 1. knowing the DS uniquely identifies the derivation tree.