Recently, <cite>Wang et al. (2019)</cite> introduced an embedding alignment approach to enable continual learning for relation extraction models. <cite>They</cite> consider a setting with streaming tasks, where each task consists of a number of distinct relations, and proposed to align the representation of relation instances in the embedding space to enable continual learning of new relations without forgetting knowledge from past relations.