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MatKG: An autonomously generated knowledge graph in Material Science

Authors: Vineeth Venugopal,Elsa Olivetti
Publisher: Springer Science and Business Media LLC
Publish date: 2024-2-17
ISSN: 2052-4463 DOI: 10.1038/s41597-024-03039-z
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The paper mentions that MatKG includes over 70,000 entities and 5.4 million unique triples after data cleaning, but the initial extraction yielded around half a million entities and 11 million triples. Given the significant reduction in data volume during cleaning, how were potential biases introduced by the cleaning process (e.g., removal of non-ASCII entities, fuzzy clustering, and ChatGPT standardization) evaluated, and what steps were taken to ensure that critical information was not lost or misrepresented in the final knowledge graph?

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