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Unleash GPT-2 Power for Event Detection
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
Event Detection (ED) aims to recognize mentions of events (i.e., event triggers) and their types in text. Recently, several ED datasets in various domains have been proposed. However, the major limitation of these resources is the lack of enough training data for individual event types which hinders the efficient training of data-hungry deep learning models. To overcome this issue, we propose to exploit the powerful pre-trained language model GPT-2 to generate training samples for ED. Todoi:10.18653/v1/2021.acl-long.490 fatcat:uxph2xg3erhobm3jvolkxjz7tu