Extracting a Knowledge Base of Mechanisms from COVID-19 Papers

Tom Hope, Aida Amini, David Wadden, Madeleine van Zuylen, Sravanthi Parasa, Eric Horvitz, Daniel Weld, Roy Schwartz, Hannaneh Hajishirzi


Abstract
The COVID-19 pandemic has spawned a diverse body of scientific literature that is challenging to navigate, stimulating interest in automated tools to help find useful knowledge. We pursue the construction of a knowledge base (KB) of mechanisms—a fundamental concept across the sciences, which encompasses activities, functions and causal relations, ranging from cellular processes to economic impacts. We extract this information from the natural language of scientific papers by developing a broad, unified schema that strikes a balance between relevance and breadth. We annotate a dataset of mechanisms with our schema and train a model to extract mechanism relations from papers. Our experiments demonstrate the utility of our KB in supporting interdisciplinary scientific search over COVID-19 literature, outperforming the prominent PubMed search in a study with clinical experts. Our search engine, dataset and code are publicly available.
Anthology ID:
2021.naacl-main.355
Volume:
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Month:
June
Year:
2021
Address:
Online
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
4489–4503
Language:
URL:
https://aclanthology.org/2021.naacl-main.355
DOI:
10.18653/v1/2021.naacl-main.355
Bibkey:
Cite (ACL):
Tom Hope, Aida Amini, David Wadden, Madeleine van Zuylen, Sravanthi Parasa, Eric Horvitz, Daniel Weld, Roy Schwartz, and Hannaneh Hajishirzi. 2021. Extracting a Knowledge Base of Mechanisms from COVID-19 Papers. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 4489–4503, Online. Association for Computational Linguistics.
Cite (Informal):
Extracting a Knowledge Base of Mechanisms from COVID-19 Papers (Hope et al., NAACL 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.naacl-main.355.pdf
Code
 dwadden/dygiepp +  additional community code
Data
CORD-19SciERC