Event Process Typing via Hierarchical Optimal Transport
Keywords:SNLP: Sentence-Level Semantics and Textual Inference
AbstractUnderstanding intention behind event processes in texts is important to many applications. One challenging task in this line is event process typing, which aims to tag the process with one action label and one object label describing the overall action of the process and object the process likely affects respectively. To tackle this task, existing methods mainly rely on the matching of the event process level and label level representation, which ignores two important characteristics: Process Hierarchy and Label Hierarchy. In this paper, we propose a Hierarchical Optimal Transport (HOT) method to address the above problem. Specifically, we first explicitly extract the process hierarchy and label hierarchy. Then the HOT optimally matches the two types of hierarchy. Experimental results show that our model outperforms the baseline models, illustrating the effectiveness of our model.
How to Cite
Zhou, B., Chen, Y., Liu, K., & Zhao, J. (2023). Event Process Typing via Hierarchical Optimal Transport. Proceedings of the AAAI Conference on Artificial Intelligence, 37(11), 14038-14046. https://doi.org/10.1609/aaai.v37i11.26643
AAAI Technical Track on Speech & Natural Language Processing