Using Linguistic Features to Improve the Generalization Capability of Neural Coreference Resolvers (D18-1)
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| Challenge: | Recent coreference resolvers have notable improvements on the CoNLL evaluation sets, but struggle to generalize properly to new datasets. |
| Approach: | They investigate the role of linguistic features in building more generalizable coreference resolvers . they show that employing features and subsets of their values that are informative for coreference resolution improves generalization . |
| Outcome: | The proposed system achieves state-of-the-art results on WikiCoref, compared with a system trained on CoNLL. |
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