  We introduce recurrent neural network grammars, probabilistic models of
sentences with explicit phrase structure. We explain efficient inference
procedures that allow application to both parsing and language modeling.
Experiments show that they provide better parsing in English than any single
previously published supervised generative model and better language modeling
than state-of-the-art sequential RNNs in English and Chinese.
