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Automatic extraction of materials and properties from superconductors scientific literature. (arXiv:2210.15600v2 [cs.CL] UPDATED)
Nov. 24, 2022, 7:13 a.m. | Luca Foppiano, Pedro Baptista de Castro, Pedro Ortiz Suarez, Kensei Terashima, Yoshihiko Takano, Masashi Ishii
cs.LG updates on arXiv.org arxiv.org
The automatic extraction of materials and related properties from the
scientific literature is gaining attention in data-driven materials science
(Materials Informatics). In this paper, we discuss Grobid-superconductors, our
solution for automatically extracting superconductor material names and
respective properties from text. Built as a Grobid module, it combines machine
learning and heuristic approaches in a multi-step architecture that supports
input data as raw text or PDF documents. Using Grobid-superconductors, we built
SuperCon2, a database of 40324 materials and properties records from …
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