Named Entity Recognition and Normalization Applied to Large-Scale Information Extraction from the Materials Science Literature

Journal of Chemical Information and Modeling
L WestonA Jain

Abstract

The number of published materials science articles has increased manyfold over the past few decades. Now, a major bottleneck in the materials discovery pipeline arises in connecting new results with the previously established literature. A potential solution to this problem is to map the unstructured raw text of published articles onto structured database entries that allow for programmatic querying. To this end, we apply text mining with named entity recognition (NER) for large-scale information extraction from the published materials science literature. The NER model is trained to extract summary-level information from materials science documents, including inorganic material mentions, sample descriptors, phase labels, material properties and applications, as well as any synthesis and characterization methods used. Our classifier achieves an accuracy (f1) of 87%, and is applied to information extraction from 3.27 million materials science abstracts. We extract more than 80 million materials-science-related named entities, and the content of each abstract is represented as a database entry in a structured format. We demonstrate that simple database queries can be used to answer complex "meta-questions" of the published literat...Continue Reading

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Citations

Jul 19, 2020·Nature Communications·Alain C VaucherTeodoro Laino
Mar 6, 2021·IScience·Olga KononovaGerbrand Ceder
Mar 17, 2021·Journal of Chemical Information and Modeling·Olga A TarasovaVladimir V Poroikov
Jun 25, 2021·Chemical Science·Filip T SzczypińskiKim E Jelfs
Apr 15, 2020·Journal of Chemical Information and Modeling·Anna M HiszpanskiThomas Yong-Jin Han
Jan 8, 2020·Journal of Chemical Information and Modeling·Edward KimElsa Olivetti
Sep 17, 2021·Journal of Chemical Information and Modeling·Juraj MavračićJacqueline M Cole
Nov 10, 2021·Journal of Chemical Information and Modeling·Pranav Shetty, Rampi Ramprasad
Mar 9, 2020··Jens HummelshøjMuratahan Aykol

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