Recently, <cite>Wang et al. (2019)</cite> introduced an embedding alignment approach to enable continual learning for relation extraction models. While <cite>they</cite> obtained promising results, a key weakness of the approach is that the use of an alignment model introduces additional parameters to already overparameterized relation extraction models, which may in turn lead to an increase in the quantity of supervision required for training.