Large language models for knowledge graph extraction from tables in materials science
Digital Discovery, vol. 4, pp. 1221–1231
Abstract
Large language models are promising tools for unifying scattered data, extracting information, and creating knowledge graphs.
Authors 3
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Max Dreger corresponding
Affiliation as printed
Theory and Computation of Energy Materials (IET-3), Institute of Energy Technologies, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
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Affiliation as printed
Centre for Advanced Simulation and Analytics (CASA), Simulation and Data Lab for Energy Materials, Forschungszentrum Jülich, 52425 Jülich, Germany
Theory and Computation of Energy Materials (IET-3), Institute of Energy Technologies, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
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Michael Hermann Eikerling Aachen Chair of Theory and Computation of Energy Materials Faculty of Georesources and Materials Engineering
RWTH Aachen University · Forschungszentrum Jülich
Affiliation as printed
Centre for Advanced Simulation and Analytics (CASA), Simulation and Data Lab for Energy Materials, Forschungszentrum Jülich, 52425 Jülich, Germany
Chair of Theory and Computation of Energy Materials, Faculty of Georesources and Materials Engineering, RWTH Aachen University, 52062 Aachen, Germany
Theory and Computation of Energy Materials (IET-3), Institute of Energy Technologies, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany
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