Dialogue focus tracking for zero pronoun resolution

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Abstract

We take a novel approach to zero pronoun resolution in Chinese: our model explicitly tracks the flow of focus in a discourse. Our approach, which generalizes to deictic references, is not reliant on the presence of overt noun phrase antecedents to resolve to, and allows us to address the large percentage of "non-anaphoric" pronouns filtered out in other approaches. We furthermore train our model using readily available parallel Chinese/English corpora, allowing for training without hand-annotated data. Our results demonstrate improvements on two test sets, as well as the usefulness of linguistically motivated features.

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APA

Rao, S., Ettinger, A., Daumé, H., & Resnik, P. (2015). Dialogue focus tracking for zero pronoun resolution. In NAACL HLT 2015 - 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference (pp. 494–503). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/n15-1052

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