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arXiv · 2311.05601

FAMuS: Frames Across Multiple Sources

Siddharth Vashishtha·Alexander Martin·William Gantt·Benjamin Van Durme·Aaron Steven White
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Abstract

Understanding event descriptions is a central aspect of language processing, but current approaches focus overwhelmingly on single sentences or documents. Aggregating information about an event \emph{across documents} can offer a much richer understanding. To this end, we present FAMuS, a new corpus of Wikipedia passages that \emph{report} on some event, paired with underlying, genre-diverse (non-Wikipedia) \emph{source} articles for the same event. Events and (cross-sentence) arguments in both report and source are annotated against FrameNet, providing broad coverage of different event types. We present results on two key event understanding tasks enabled by FAMuS: \emph{source validation} -- determining whether a document is a valid source for a target report event -- and \emph{cross-document argument extraction} -- full-document argument extraction for a target event from both its report and the correct source article. We release both FAMuS and our models to support further research.

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Siddharth Vashishtha, Alexander Martin, William Gantt, Benjamin Van Durme, Aaron Steven White. 2023-11-09. FAMuS: Frames Across Multiple Sources. https://arxiv.org/abs/2311.05601

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