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Could someone explain the results of this, rather than the code and the theory?

• newsposter123 11y ago
  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.