Document-Level Event Extraction Based on Frame Semantic Mapping and Type Awareness
Document-Level event extraction,consisting of two subtasks of event detection and argument identifica-tion,identifies the event type and event arguments from a given text.This paper proposes a document-level event extraction method based on frame semantic mapping and type-awareness.To leverage the similar structure in frame semantic nets,a mapping is established between Chinese FrameNet(CFN)and Chinese text events.The trigger word interpretation information and the sliding window mechanism are introduced to fully perceive the context infor-mation in the text input layer.A multi-event separation strategy based on type-aware labels alleviates the problem of argument-coupling.In order to improve the robustness of the model,adversarial training is further introduced.Ex-perimental results on DuEE-fin and CCKS2021 datasets show that the proposed method has a significant improved performance compared with the current mainstream models.
Chinese FrameNetframe semantic mappingtype awarenessevent extraction
万方数据
维普
