NEREL-BIO: a dataset of biomedical abstracts annotated with nested named entities
Abstract 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 gene...
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Veröffentlicht in: | Bioinformatics (Oxford, England) England), 2023-04, Vol.39 (4) |
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container_title | Bioinformatics (Oxford, England) |
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creator | Loukachevitch, Natalia Manandhar, Suresh Baral, Elina Rozhkov, Igor Braslavski, Pavel Ivanov, Vladimir Batura, Tatiana Tutubalina, Elena |
description | Abstract
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 → NEREL-BIO) and cross-language (English → 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. |
doi_str_mv | 10.1093/bioinformatics/btad161 |
format | Article |
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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 → NEREL-BIO) and cross-language (English → 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.</description><identifier>ISSN: 1367-4811</identifier><identifier>ISSN: 1367-4803</identifier><identifier>EISSN: 1367-4811</identifier><identifier>DOI: 10.1093/bioinformatics/btad161</identifier><identifier>PMID: 37004189</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Language ; Natural Language Processing ; Original Paper ; PubMed ; Semantics</subject><ispartof>Bioinformatics (Oxford, England), 2023-04, Vol.39 (4)</ispartof><rights>The Author(s) 2023. Published by Oxford University Press. 2023</rights><rights>The Author(s) 2023. Published by Oxford University Press.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c457t-4c5e3ab0c71d31fd326859b0a19e6131830617882c9b35bf52b6dab94e74909a3</citedby><cites>FETCH-LOGICAL-c457t-4c5e3ab0c71d31fd326859b0a19e6131830617882c9b35bf52b6dab94e74909a3</cites><orcidid>0000-0001-7936-0284 ; 0000-0003-4333-7888</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10129873/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10129873/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,1603,27923,27924,53790,53792</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37004189$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Lu, Zhiyong</contributor><creatorcontrib>Loukachevitch, Natalia</creatorcontrib><creatorcontrib>Manandhar, Suresh</creatorcontrib><creatorcontrib>Baral, Elina</creatorcontrib><creatorcontrib>Rozhkov, Igor</creatorcontrib><creatorcontrib>Braslavski, Pavel</creatorcontrib><creatorcontrib>Ivanov, Vladimir</creatorcontrib><creatorcontrib>Batura, Tatiana</creatorcontrib><creatorcontrib>Tutubalina, Elena</creatorcontrib><title>NEREL-BIO: a dataset of biomedical abstracts annotated with nested named entities</title><title>Bioinformatics (Oxford, England)</title><addtitle>Bioinformatics</addtitle><description>Abstract
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 → NEREL-BIO) and cross-language (English → 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.</description><subject>Language</subject><subject>Natural Language Processing</subject><subject>Original Paper</subject><subject>PubMed</subject><subject>Semantics</subject><issn>1367-4811</issn><issn>1367-4803</issn><issn>1367-4811</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><sourceid>EIF</sourceid><recordid>eNqNUU1LAzEUDKJorf4FydHL2rzNfsWLaKlaKBZFz-Elm9XIdlM3qeK_N9Iq9ebpDbx5M_MYQk6AnQETfKSss13j-gUGq_1IBayhgB0yAF6USVYB7G7hA3Lo_StjLGd5sU8OeMlYBpUYkPu7ycNkllxN5-cUaY0BvQnUNTQaLExtNbYUlQ896uApdp0LGExNP2x4oZ3x37jDyKSmCzZY44_IXoOtN8ebOSRP15PH8W0ym99Mx5ezRGd5GZJM54ajYrqEmkNT87SocqEYgjAFcKg4K6CsqlQLxXPV5KkqalQiM2UmmEA-JBdr3eVKRX8d_Xts5bK3C-w_pUMr_246-yKf3bsEBqmoSh4VTjcKvXtbxV_kwnpt2hY741ZepqXgIoaKWYakWFN177zvTfPrA0x-FyL_FiI3hcTDk-2Uv2c_DUQCrAlutfyv6BfLRp7q</recordid><startdate>20230403</startdate><enddate>20230403</enddate><creator>Loukachevitch, Natalia</creator><creator>Manandhar, Suresh</creator><creator>Baral, Elina</creator><creator>Rozhkov, Igor</creator><creator>Braslavski, Pavel</creator><creator>Ivanov, Vladimir</creator><creator>Batura, Tatiana</creator><creator>Tutubalina, Elena</creator><general>Oxford University Press</general><scope>TOX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-7936-0284</orcidid><orcidid>https://orcid.org/0000-0003-4333-7888</orcidid></search><sort><creationdate>20230403</creationdate><title>NEREL-BIO: a dataset of biomedical abstracts annotated with nested named entities</title><author>Loukachevitch, Natalia ; Manandhar, Suresh ; Baral, Elina ; Rozhkov, Igor ; Braslavski, Pavel ; Ivanov, Vladimir ; Batura, Tatiana ; Tutubalina, Elena</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c457t-4c5e3ab0c71d31fd326859b0a19e6131830617882c9b35bf52b6dab94e74909a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Language</topic><topic>Natural Language Processing</topic><topic>Original Paper</topic><topic>PubMed</topic><topic>Semantics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Loukachevitch, Natalia</creatorcontrib><creatorcontrib>Manandhar, Suresh</creatorcontrib><creatorcontrib>Baral, Elina</creatorcontrib><creatorcontrib>Rozhkov, Igor</creatorcontrib><creatorcontrib>Braslavski, Pavel</creatorcontrib><creatorcontrib>Ivanov, Vladimir</creatorcontrib><creatorcontrib>Batura, Tatiana</creatorcontrib><creatorcontrib>Tutubalina, Elena</creatorcontrib><collection>Oxford Journals Open Access Collection</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Bioinformatics (Oxford, England)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Loukachevitch, Natalia</au><au>Manandhar, Suresh</au><au>Baral, Elina</au><au>Rozhkov, Igor</au><au>Braslavski, Pavel</au><au>Ivanov, Vladimir</au><au>Batura, Tatiana</au><au>Tutubalina, Elena</au><au>Lu, Zhiyong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>NEREL-BIO: a dataset of biomedical abstracts annotated with nested named entities</atitle><jtitle>Bioinformatics (Oxford, England)</jtitle><addtitle>Bioinformatics</addtitle><date>2023-04-03</date><risdate>2023</risdate><volume>39</volume><issue>4</issue><issn>1367-4811</issn><issn>1367-4803</issn><eissn>1367-4811</eissn><abstract>Abstract
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 → NEREL-BIO) and cross-language (English → 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.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>37004189</pmid><doi>10.1093/bioinformatics/btad161</doi><orcidid>https://orcid.org/0000-0001-7936-0284</orcidid><orcidid>https://orcid.org/0000-0003-4333-7888</orcidid><oa>free_for_read</oa></addata></record> |
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source | MEDLINE; DOAJ Directory of Open Access Journals; Oxford Journals Open Access Collection; EZB-FREE-00999 freely available EZB journals; PubMed Central; Alma/SFX Local Collection |
subjects | Language Natural Language Processing Original Paper PubMed Semantics |
title | NEREL-BIO: a dataset of biomedical abstracts annotated with nested named entities |
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