Recently end-to-end models have outperformed traditional pipeline approaches, predicting syntactic or semantic structure as intermediate steps, on NLU tasks such as sentiment analysis and semantic relatedness (Le and Mikolov, 2014;Kiros et al., 2015), question answering  and textual entailment (Rocktäschel et al., 2015).
the linguistic structure used in applications has predominantly been shallow, restricted to bilexical dependencies or trees.