Distilling Discrimination and Generalization Knowledge for Event Detection via Delta-Representation Learning
Yaojie Lu, Hongyu Lin, Xianpei Han, Le Sun · 2019
Event detection systems rely on discrimination knowledge to distinguish ambiguous trigger words and generalization knowledge to detect unseen/sparse trigger words.Current neural event detection approaches focus on trigger-centric representations, which work well on distilling discrimination knowledge, but poorly on learning generalization knowledge.To address this problem, this paper proposes a ∆-learning approach to distill discrimination and generalization knowledge by effectively decoupling, incrementally learning and adaptively fusing event representation.Experiments show that our method significantly outperforms previous approaches on unseen/sparse trigger words, and achieves state-of-the-art performance on both ACE2005 and KBP2017 datasets.