Event extraction is a key research area in information extraction. To improve the effect of event extraction and solve the problem that general event extraction methods cannot make full use of text feature information, an event extraction method fused with trigger word features is proposed. A remote trigger word database is constructed to provide additional feature information for the event classification model and enhance the discovery ability of event trigger words. Then, the event type and the distance features of trigger words are integrated to improve the representation and learning ability of the event element extraction model. Finally, the event classification model and the event element extraction model are connected in series to improve the event extraction effect. Experiments on the DuEE dataset demonstrate that compared with other models, this model improves the accuracy, recall, and F1 value, which proves the effectiveness of this model.