Event extraction enhanced by fusing trigger feature

Abstract

Event extraction is a key research direction in the field of information extraction. In order to improve the effect of event extraction and solve the problem that the general event extraction method cannot make full use of the text feature information, an event extraction method integrating trigger word features is proposed. By building a remote trigger thesaurus, we can provide additional feature information for the event type classification model, enhance the ability of discovering event trigger words. Then the event arguments extraction model integrates the event type and trigger distance features to improve the representation learning ability. Finally, connecting the event type classification model and the event arguments extraction model in series to complete event extraction. Experiments are carried out on the DuEE dataset and the result shows that our model has more outstanding performance than other models.