Type Hierarchy Enhanced Event Detection without Triggers

Youcheng Yan, Zhao Liu,Feng Gao,Jinguang Gu

APPLIED SCIENCES-BASEL(2023)

引用 0|浏览4
暂无评分
摘要
Event detection (ED) aims to detect events from a given text and categorize them into event types. Most of the current approaches to ED rely heavily on the human annotations of triggers, which are often costly and affect the application of ED in other fields. However, triggers are not necessary for the event detection task. We propose a novel framework called Type Hierarchy Enhanced Event Detection Without Triggers (THEED) to avoid this problem. More specifically, We construct a type hierarchy concept module using the external knowledge graph Probase to enhance the semantic representation of event types. In addition, we divide input instances into word-level and context-level representations, which can make the model use different level features. The experimental result indicates that our proposed approach achieves better improvement. Additionally, it is significantly competitive with mainstream trigger-based models.
更多
查看译文
关键词
hierarchy concept,attention mechanism,probase,bi-LSTM,event detection
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要