Leveraging Annotators’ Gaze Behaviour for Coreference Resolution
نویسندگان
چکیده
This paper aims at utilizing cognitive information obtained from the eye movements behavior of annotators for automatic coreference resolution. We first record eye-movement behavior of multiple annotators resolving coreferences in 22 documents selected from MUC dataset. By inspecting the gaze-regression profiles of our participants, we observe how regressive saccades account for selection of potential antecedents for a certain anaphoric mention. Based on this observation, we then propose a heuristic to utilize gaze data to prune mention pairs in mention-pair model, a popular paradigm for automatic coreference resolution. Consistent improvement in accuracy across several classifiers is observed with our heuristic, demonstrating why cognitive data can be useful for a difficult task like coreference resolution.
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