Intuitively, when the distance similarity p between two relational instances equals 0.5, there is a high prob-ability that at least one of two instances is near the decision boundary between relation clusters.
we use the conditional entropy loss (Grandvalet and Bengio, 2005), which reaches the maximum when p = 0.5, to penalize close-boundary distribution of data points: Virtual Adversarial Loss.