Sentiment grammars provides a principled way for explicitly modeling sentiment composition, and through parameterizing the emission rules with neural encoders, it can take the advantage of deep learning.
by adding a weighted grammar on top of a tree-LSTM, our model is reminiscent of LSTM-CRF in the sequence structure.