SynNER: syntax-infused named entity recognition in the biomedical domain

Syntactic features improve NER accuracy in attention-based neural systems, and parsing as sequence labelling brings additional benefits.

Authors

Olga Zamaraeva (ORCID: https://orcid.org/0000-0001-9969-058X)
Muhammad Imran (ORCID: https://orcid.org/0000-0001-7596-3651)
Carlos Gómez-Rodríguez

Institutions

Universidade da Coruña (ES)

Publication Details

Journal: JAMIA Open
Published: 2025-10-21
DOI: https://doi.org/10.1093/jamiaopen/ooaf149
Primary Topic: Topic Modeling
Type: article
Field-Weighted Citation Impact: 0.00

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article

SynNER: syntax-infused named entity recognition in the biomedical domain

Olga Zamaraeva, Muhammad Imran, Carlos Gómez-Rodríguez

Oct 21, 2025

JAMIA Open

Topic Modeling

article

SynNER: syntax-infused named entity recognition in the biomedical domain

Olga Zamaraeva, Muhammad Imran, Carlos Gómez-Rodríguez

October 21, 2025article en

Abstract

Syntactic features improve NER accuracy in attention-based neural systems, and parsing as sequence labelling brings additional benefits.

JAMIA OpenVol. 9(1)

Universidade da Coruña (ES)

Quality Education

Openalex Percentile: Top 14%

Topic Modeling

DOI Open Access PDF OpenAlex

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SynNER: syntax-infused named entity recognition in the biomedical domain — Olga Zamaraeva, Muhammad Imran, et al. · JAMIA Open (2025) | TGRS Research Map | TGRS