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        <title>Improving Romanian BioNER Using a Biologically Inspired System</title>
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        <namePart type="given">Maria</namePart>
        <namePart type="family">Mitrofan</namePart>
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        <namePart type="given">Vasile</namePart>
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            <title>Proceedings of the 21st Workshop on Biomedical Language Processing</title>
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        <name type="personal">
            <namePart type="given">Dina</namePart>
            <namePart type="family">Demner-Fushman</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Kevin</namePart>
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            <namePart type="family">Cohen</namePart>
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        <name type="personal">
            <namePart type="given">Sophia</namePart>
            <namePart type="family">Ananiadou</namePart>
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        <name type="personal">
            <namePart type="given">Junichi</namePart>
            <namePart type="family">Tsujii</namePart>
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    <abstract>Recognition of named entities present in text is an important step towards information extraction and natural language understanding. This work presents a named entity recognition system for the Romanian biomedical domain. The system makes use of a new and extended version of SiMoNERo corpus, that is open sourced. Also, the best system is available for direct usage in the RELATE platform.</abstract>
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    <identifier type="doi">10.18653/v1/2022.bionlp-1.30</identifier>
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%0 Conference Proceedings
%T Improving Romanian BioNER Using a Biologically Inspired System
%A Mitrofan, Maria
%A Pais, Vasile
%Y Demner-Fushman, Dina
%Y Cohen, Kevin Bretonnel
%Y Ananiadou, Sophia
%Y Tsujii, Junichi
%S Proceedings of the 21st Workshop on Biomedical Language Processing
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F mitrofan-pais-2022-improving
%X Recognition of named entities present in text is an important step towards information extraction and natural language understanding. This work presents a named entity recognition system for the Romanian biomedical domain. The system makes use of a new and extended version of SiMoNERo corpus, that is open sourced. Also, the best system is available for direct usage in the RELATE platform.
%R 10.18653/v1/2022.bionlp-1.30
%U https://aclanthology.org/2022.bionlp-1.30/
%U https://doi.org/10.18653/v1/2022.bionlp-1.30
%P 316-322

Markdown (Informal)

[Improving Romanian BioNER Using a Biologically Inspired System](https://aclanthology.org/2022.bionlp-1.30/) (Mitrofan & Pais, BioNLP 2022)

• Improving Romanian BioNER Using a Biologically Inspired System (Mitrofan & Pais, BioNLP 2022)

ACL

• Maria Mitrofan and Vasile Pais. 2022. Improving Romanian BioNER Using a Biologically Inspired System. In Proceedings of the 21st Workshop on Biomedical Language Processing, pages 316–322, Dublin, Ireland. Association for Computational Linguistics.