The central idea behind this approach is exploiting the power of recurrent neural networks to let the model decide what apsects of sentence context are important to making parsing decisions, rather than relying on fallible linguistic information (which moreover requires leaving out information which could be useful).
we model an input sentence using Long Short-Term Memory networks (LSTM), which have made a recent resurgence after being initially formulated by Hochreiter and Schmidhuber (1997).