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NEREL-BIO: a dataset of biomedical abstracts annotated with nested named entities
MOTIVATION: This article describes NEREL-BIO—an annotation scheme and corpus of PubMed abstracts in Russian and smaller number of abstracts in English. NEREL-BIO extends the general domain dataset NEREL by introducing domain-specific entity types. NEREL-BIO annotation scheme covers both general and...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10129873/ https://www.ncbi.nlm.nih.gov/pubmed/37004189 http://dx.doi.org/10.1093/bioinformatics/btad161 |
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author | Loukachevitch, Natalia Manandhar, Suresh Baral, Elina Rozhkov, Igor Braslavski, Pavel Ivanov, Vladimir Batura, Tatiana Tutubalina, Elena |
author_facet | Loukachevitch, Natalia Manandhar, Suresh Baral, Elina Rozhkov, Igor Braslavski, Pavel Ivanov, Vladimir Batura, Tatiana Tutubalina, Elena |
author_sort | Loukachevitch, Natalia |
collection | PubMed |
description | MOTIVATION: This article describes NEREL-BIO—an annotation scheme and corpus of PubMed abstracts in Russian and smaller number of abstracts in English. NEREL-BIO extends the general domain dataset NEREL by introducing domain-specific entity types. NEREL-BIO annotation scheme covers both general and biomedical domains making it suitable for domain transfer experiments. NEREL-BIO provides annotation for nested named entities as an extension of the scheme employed for NEREL. Nested named entities may cross entity boundaries to connect to shorter entities nested within longer entities, making them harder to detect. RESULTS: NEREL-BIO contains annotations for 700+ Russian and 100+ English abstracts. All English PubMed annotations have corresponding Russian counterparts. Thus, NEREL-BIO comprises the following specific features: annotation of nested named entities, it can be used as a benchmark for cross-domain (NEREL [Formula: see text] NEREL-BIO) and cross-language (English [Formula: see text] Russian) transfer. We experiment with both transformer-based sequence models and machine reading comprehension models and report their results. AVAILABILITY AND IMPLEMENTATION: The dataset and annotation guidelines are freely available at https://github.com/nerel-ds/NEREL-BIO. |
format | Online Article Text |
id | pubmed-10129873 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-101298732023-04-27 NEREL-BIO: a dataset of biomedical abstracts annotated with nested named entities Loukachevitch, Natalia Manandhar, Suresh Baral, Elina Rozhkov, Igor Braslavski, Pavel Ivanov, Vladimir Batura, Tatiana Tutubalina, Elena Bioinformatics Original Paper MOTIVATION: This article describes NEREL-BIO—an annotation scheme and corpus of PubMed abstracts in Russian and smaller number of abstracts in English. NEREL-BIO extends the general domain dataset NEREL by introducing domain-specific entity types. NEREL-BIO annotation scheme covers both general and biomedical domains making it suitable for domain transfer experiments. NEREL-BIO provides annotation for nested named entities as an extension of the scheme employed for NEREL. Nested named entities may cross entity boundaries to connect to shorter entities nested within longer entities, making them harder to detect. RESULTS: NEREL-BIO contains annotations for 700+ Russian and 100+ English abstracts. All English PubMed annotations have corresponding Russian counterparts. Thus, NEREL-BIO comprises the following specific features: annotation of nested named entities, it can be used as a benchmark for cross-domain (NEREL [Formula: see text] NEREL-BIO) and cross-language (English [Formula: see text] Russian) transfer. We experiment with both transformer-based sequence models and machine reading comprehension models and report their results. AVAILABILITY AND IMPLEMENTATION: The dataset and annotation guidelines are freely available at https://github.com/nerel-ds/NEREL-BIO. Oxford University Press 2023-04-02 /pmc/articles/PMC10129873/ /pubmed/37004189 http://dx.doi.org/10.1093/bioinformatics/btad161 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Paper Loukachevitch, Natalia Manandhar, Suresh Baral, Elina Rozhkov, Igor Braslavski, Pavel Ivanov, Vladimir Batura, Tatiana Tutubalina, Elena NEREL-BIO: a dataset of biomedical abstracts annotated with nested named entities |
title | NEREL-BIO: a dataset of biomedical abstracts annotated with nested named entities |
title_full | NEREL-BIO: a dataset of biomedical abstracts annotated with nested named entities |
title_fullStr | NEREL-BIO: a dataset of biomedical abstracts annotated with nested named entities |
title_full_unstemmed | NEREL-BIO: a dataset of biomedical abstracts annotated with nested named entities |
title_short | NEREL-BIO: a dataset of biomedical abstracts annotated with nested named entities |
title_sort | nerel-bio: a dataset of biomedical abstracts annotated with nested named entities |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10129873/ https://www.ncbi.nlm.nih.gov/pubmed/37004189 http://dx.doi.org/10.1093/bioinformatics/btad161 |
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