To further alleviate the effect of wrong labeling problem, soft-label training algorithm (Liu et al., 2017b), reinforcement learning methods (Feng et al., 2018;Qin et al., 2018b) and additional side information (Vashishth et al., 2018;Wang et al., 2018) have been used.
a former negative instance has a big chance to be credible negative if any of its entities is not mentioned in the description of the other one.