In this paper, we propose a goal-directed endto-end deep reinforcement learning framework to resolve coreference as shown in Figure 1.
we leverage the neural architecture in  as our policy network, which includes learning span representation, scoring potential entity mentions, and generating a probability distribution over all possible coreference linking actions from the current mention to its antecedents.