Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank

  title={Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank},
  author={Richard Socher and Alex Perelygin and Jean Wu and Jason Chuang and Christopher D. Manning and Andrew Y. Ng and Christopher Potts},
Semantic word spaces have been very useful but cannot express the meaning of longer phrases in a principled way. Further progress towards understanding compositionality in tasks such as sentiment detection requires richer supervised training and evaluation resources and more powerful models of composition. To remedy this, we introduce a Sentiment Treebank. It includes fine grained sentiment labels for 215,154 phrases in the parse trees of 11,855 sentences and presents new challenges for… CONTINUE READING
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