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The authors introduce NSF-SciFy, a large-scale dataset of 2.8 million scientific claims and investigation proposals extracted from NSF award abstracts. They use zero-shot prompting to extract claims and proposals, creating subsets focused on materials science and a balanced set across NSF directorates. Fine-tuning language models on NSF-SciFy significantly improves performance on non-technical abstract generation, claim extraction, and investigation proposal extraction, with gains exceeding 100% for extraction tasks.
Forget small datasets: NSF-SciFy delivers 2.8 million scientific claims ready to fuel a new wave of research in claim verification and scientific discovery.
We introduce NSF-SciFy, a comprehensive dataset of scientific claims and investigation proposals extracted from National Science Foundation award abstracts. While previous scientific claim verification datasets have been limited in size and scope, NSF-SciFy represents a significant advance with 2.8 million claims from 400,000 abstracts spanning all science and mathematics disciplines. We present two focused subsets: NSF-SciFy-MatSci with 114,000 claims from materials science awards, and NSF-SciFy-20K with 135,000 claims across five NSF directorates. Using zero-shot prompting, we develop a scalable approach for joint extraction of scientific claims and investigation proposals. We demonstrate the dataset's utility through three downstream tasks: non-technical abstract generation, claim extraction, and investigation proposal extraction. Fine-tuning language models on our dataset yields substantial improvements, with relative gains often exceeding 100%, particularly for claim and proposal extraction tasks. Our error analysis reveals that extracted claims exhibit high precision but lower recall, suggesting opportunities for further methodological refinement. NSF-SciFy enables new research directions in large-scale claim verification, scientific discovery tracking, and meta-scientific analysis. Code and data are available at https://github.com/darpa-scify/NSFSciFy.
