SCoNE: a Self-Correcting and Noise-Augmented Method for Complex Biological and Chemical Named Entity Recognition

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SPIRE - Sciences Po Institutional REpository
Published
2026-03-24
Primary Topic
Biomedical Text Mining and Ontologies
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article
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article

SCoNE: a Self-Correcting and Noise-Augmented Method for Complex Biological and Chemical Named Entity Recognition

László Vidács, Balázs Nagy, Claire Nédellec, Xingyu Zhu et al.
SPIRE - Sciences Po Institutional REpository
Biomedical Text Mining and Ontologies
article

SCoNE: a Self-Correcting and Noise-Augmented Method for Complex Biological and Chemical Named Entity Recognition

László Vidács, Balázs Nagy, Claire Nédellec, Xingyu Zhu, Robert Bossy
article en

Abstract

No abstract available for this paper.
SPIRE - Sciences Po Institutional REpository
University of Szeged (HU), HUN-REN Szegedi Biológiai Kutatóközpont (HU), Mathématiques et Informatique Appliquées du Génome à l'Environnement (FR)
European Commission, HORIZON EUROPE Framework Programme
Openalex Percentile: Top 29%
Biomedical Text Mining and Ontologies
Open Access PDFOpenAlex
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SCoNE: a Self-Correcting and Noise-Augmented Method for Complex Biological and Chemical Named Entity Recognition — László Vidács, Balázs Nagy, et al. · SPIRE - Sciences Po Institutional REpository (2026) | TGRS Research Map | TGRS