Event Extraction by Answering (Almost) Natural Questions
Xinya Du, Claire Cardie · 2020
The problem of event extraction requires detecting the event trigger and extracting its corresponding arguments.Existing work in event argument extraction typically relies heavily on entity recognition as a preprocessing/concurrent step, causing the well-known problem of error propagation.To avoid this issue, we introduce a new paradigm for event extraction by formulating it as a question answering (QA) task that extracts the event arguments in an end-to-end manner.Empirical results demonstrate that our framework outperforms prior methods substantially; in addition, it is capable of extracting event arguments for roles not seen at training time (i.e., in a zeroshot learning setting).1