  This paper describes our winning contribution to SemEval 2018 Task 4:
Character Identification on Multiparty Dialogues. It is a simple, standard
model with one key innovation, an entity library. Our results show that this
innovation greatly facilitates the identification of infrequent characters.
Because of the generic nature of our model, this finding is potentially
relevant to any task that requires effective learning from sparse or unbalanced
data.
