In summary, our contributions are threefold: • We present a plug-and-play framework based on GAIL to enhance existing RL-based reasoning in KGs by learning reasoning policies and reward functions through imitating demonstrations.
compared to NELL-995, FB15K-237 is more challenging and closer to real-world scenarios, where its facts are created from FB15K (Bordes et al., 2013) with redundant relations removed.