Chinese Zero Pronoun Resolution: A Joint Unsupervised Discourse-Aware Model Rivaling State-of-the-Art Resolvers

We propose an unsupervised probabilistic model for zero pronoun resolution. To our knowledge, this is the first such model that (1) is trained on zero pronouns in an unsupervised manner; (2) jointly identifies and resolves anaphoric zero pronouns; and (3) exploits discourse information provided by a salience model. Experiments demonstrate that our unsupervised model significantly outperforms its state-of-the-art unsupervised counterpart when resolving the Chinese zero pronouns in the OntoNotes corpus.

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