S-LSTM can be considered as bringing the merits of a recursive neural network and a recurrent neural network togetherStanford Sentiment Tree Bank (<cite>Socher et al., 2013</cite>) to determine the sentiment for different granularities of phrases in a tree. <cite>The dataset</cite> has favorable properties: in addition to being a benchmark for much previous work, <cite>it</cite> provides with human annotations at all nodes of the trees, enabling us to comprehensively explore the properties of S-LSTM.