On the positive side, we have shown that framing models from an entity-centric perspective makes it very natural to adopt architectural decisions that are good inductive biases.
by exploiting the fact that both speakers and referents are entities, these models can do more with the same model size, improving results on less frequent entities and emulating rule-based behavior such as "a first person expression refers to the speaker".