Improving Coreference Resolution by Learning Entity-Level Distributed Representations
Table 5: Comparison with the current state-of-the-art approaches on the CoNLL 2012 test sets. NN Mention Ranker and NN Cluster Ranker are contributions of this work.
['[EMPTY]', 'MUC', 'MUC', 'MUC', 'B3', 'B3', 'B3', 'CEAF [ITALIC] ϕ4', 'CEAF [ITALIC] ϕ4', 'CEAF [ITALIC] ϕ4', '[EMPTY]']
Our mention-ranking model surpasses all previous systems. We attribute its improvement over the neural mention ranker from Wiseman et al. (2015) to our model using a deeper neural network, pretrained word embeddings, and more sophisticated pretraining.