We summarize the statistics of the datasets in Table 1  For fairness in model comparation, we use similar parameters in compared models.
we exploit 300-dimensional Glove vectors (Pennington et al., 2014) for the word embeddings, as well as a 30-dimensional part-of-speech (POS) embeddings, 30-dimensional position embeddings, which is used to identify the relative position of each word with respect to the aspect in the sentence.