In our problem setting, the model also has access to the lexical resource L = {L e | e ∈ E} where L e = (l e 1 , ..., l e k ) is the lexical definition of entity e extracted from the knowledge base.
the task of the model is to predict the correct missing entities for each empty slot in D. There are several possible ways to specify the candidate set E. For instance, we could define E so that it includes all entities found in the corpus.