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End-to-End Neural Discourse Deixis Resolution in Dialogue

2022-11-29Code Available0· sign in to hype

Shengjie Li, Vincent Ng

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Abstract

We adapt Lee et al.'s (2018) span-based entity coreference model to the task of end-to-end discourse deixis resolution in dialogue, specifically by proposing extensions to their model that exploit task-specific characteristics. The resulting model, dd-utt, achieves state-of-the-art results on the four datasets in the CODI-CRAC 2021 shared task.

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