Constrained Multi-Task Learning for Event Coreference Resolution
Jing Juan Lu, Vincent Ng · 2021
We propose a neural event coreference model in which event coreference is jointly trained with five tasks: trigger detection, entity coreference, anaphoricity determination, realis detection, and argument extraction.To guide the learning of this complex model, we incorporate cross-task consistency constraints into the learning process as soft constraints via designing penalty functions.In addition, we propose the novel idea of viewing entity coreference and event coreference as a single coreference task, which we believe is a step towards a unified model of coreference resolution.The resulting model achieves state-of-the-art results on the KBP 2017 event coreference dataset.