Identifying temporal and subevent relationships between different events (i.e., event relation extraction) is an important step towards event-centric natural language processing, which can help understand how events evolve and potentially facilitate many downstream tasks, such as timeline generation and event knowledge graph construction. Existing work has extensively leveraged external knowledge to improve the performance of relation extraction. Despite the progress made, the current knowledge-enhanced approach still has some shortcomings, e.g., knowledge missing, knowledge noise, and subopti...
