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Mad Libs Are All You Need: Augmenting Cross-Domain Document-Level Event Argument Data
March 7, 2024, 5:42 a.m. | Joseph Gatto, Parker Seegmiller, Omar Sharif, Sarah M. Preum
cs.LG updates on arXiv.org arxiv.org
Abstract: Document-Level Event Argument Extraction (DocEAE) is an extremely difficult information extraction problem -- with significant limitations in low-resource cross-domain settings. To address this problem, we introduce Mad Lib Aug (MLA), a novel generative DocEAE data augmentation framework. Our approach leverages the intuition that Mad Libs, which are categorically masked documents used as a part of a popular game, can be generated and solved by LLMs to produce data for DocEAE. Using MLA, we achieve a …
abstract arxiv augmentation cs.cl cs.lg data document domain event extraction framework generative information information extraction intuition limitations low novel type
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