Opinion Mining with Deep Recurrent Neural Networks (cs.cornell.edu)

This is from the "Conclusions" slide: • Deep recurrent nets perform better than their shallow counterparts of the same size on both DSE and ESE extraction. • Both shallow and deep RNNs capture aspects of subjectivity, but deep RNNs seem to better handle the expression boundaries. • Deep RNNs outperforms previous baselines CRF and semi-CRF without having access to the dependency or constituency trees, opinion lexicons or POS tags, even when (semi)CRF has access to word vectors.

tldr: Deep RNN's are better than shallow RNN's and CRF's for several NLP tasks.