It can be observed that in general the compositional methods perform better than the non-compositional ones (e.g., averaging, concatenation), and when the compositional method is trained on the task, we get the best performance on two out of three data sets.
our B-LSTM conv-glove gets the best results on QC3 and TA, outperforming B-GRU conv-glove by a slight margin in F 1 .