We conclude that the knowledge regularizer plays a key role in achieving the state-of-the-art performance and the knowledge layer must be used together with knowledge regularization in our framework.
we propose to tightly integrate these constraints into the discourse relation inference process by manipulating hidden word representations to reflect relations between words, and meanwhile balance attentions to contexts and constraints through adding a knowledge regularization term in the final objective function.