Visualization reveals that it is much easier for neural net models to identify and concentrate on the relevant regions of contexts using the dependency chain representation, which further verifies that additional event words in a sentential context are crucial to predict target event temporal status.
all the models were trained using RMSProp optimizer with the initial learning rate 0.001 and the same random seed.