In the iteration, the information from different perspectives is shared with each facet via the newly added facts.
after predicting the top-n h facts for each head entity, we select top-n f b (n f b < n h ) most probable facts according to the score of each triple and then feed them into the existing knowledge base for re-training the FFD model.