Event Coreference Resolution for Vietnamese News Based on Generative Adversarial Networks
Event coreference resolution is a task to analyze whether event descriptions discuss the same real event from different perspectives.However,in the same news report,there is usually a noisy situation in which different event sentences have similar contexts but no coreference relationship.To address this issue,we propose an event coreference resolution method based on generative adversarial networks.It uses the context information of trigger words as the minimum feature representation of event sentence,and adopts the generative adversarial network to construct noise data filters to distinguish information instances from noise instances.Experiments on the Vietnamese event dataset and public dataset verify the validity of the model.