Incorporating Circumstances into Narrative Event Prediction

Abstract

Aiming at discovering the event evolution, the narrative event prediction is essential to modeling sophisticated real-world events. Existing studies focus on mining the inter-events relationships while ignoring how the events happened, which we called circumstances. However, we observe that the circumstances indicate the event evolution implicitly, and are significant for the narrative event prediction. To incorporate circumstances into the narrative event prediction, we propose the CircEvent, which adopts the multi-head attention to retrieve circumstances at the local and global levels. We also introduce a regularization of attention weights to leverage the alignment between events and local circumstances. The experimental results demonstrate that CircEvent outperforms existing baselines by 12.2%. Further analysis demonstrates the effectiveness of our multi-head attention modules and regularization. Our source code is available at https://github.com/ Shichao-Wang/CircEvent.