Abstract
We describe an algorithm for a novel task: disambiguating the pronoun you in conversation. You can be generic or referential; finding referential you is important for tasks such as addressee identification or extracting ‘owners’ of action items. Our classifier achieves 84% accuracy in two-person conversations; an initial study shows promising performance even on more complex multi-party meetings.
Cite
CITATION STYLE
Gupta, S., Purver, M., & Jurafsky, D. (2007). Disambiguating between generic and referential “you” in dialog. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 105–108). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1557769.1557801
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