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        <title>MoNERo: a Biomedical Gold Standard Corpus for the Romanian Language</title>
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    <name type="personal">
        <namePart type="given">Maria</namePart>
        <namePart type="family">Mitrofan</namePart>
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    <name type="personal">
        <namePart type="given">Verginica</namePart>
        <namePart type="family">Barbu Mititelu</namePart>
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    <name type="personal">
        <namePart type="given">Grigorina</namePart>
        <namePart type="family">Mitrofan</namePart>
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            <title>Proceedings of the 18th BioNLP Workshop and Shared Task</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>
            <namePart type="given">Bretonnel</namePart>
            <namePart type="family">Cohen</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Sophia</namePart>
            <namePart type="family">Ananiadou</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Junichi</namePart>
            <namePart type="family">Tsujii</namePart>
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    <abstract>In an era when large amounts of data are generated daily in various fields, the biomedical field among others, linguistic resources can be exploited for various tasks of Natural Language Processing. Moreover, increasing number of biomedical documents are available in languages other than English. To be able to extract information from natural language free text resources, methods and tools are needed for a variety of languages. This paper presents the creation of the MoNERo corpus, a gold standard biomedical corpus for Romanian, annotated with both part of speech tags and named entities. MoNERo comprises 154,825 morphologically annotated tokens and 23,188 entity annotations belonging to four entity semantic groups corresponding to UMLS Semantic Groups.</abstract>
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    <identifier type="doi">10.18653/v1/W19-5008</identifier>
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        <date>2019-08</date>
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%0 Conference Proceedings
%T MoNERo: a Biomedical Gold Standard Corpus for the Romanian Language
%A Mitrofan, Maria
%A Barbu Mititelu, Verginica
%A Mitrofan, Grigorina
%Y Demner-Fushman, Dina
%Y Cohen, Kevin Bretonnel
%Y Ananiadou, Sophia
%Y Tsujii, Junichi
%S Proceedings of the 18th BioNLP Workshop and Shared Task
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F mitrofan-etal-2019-monero
%X In an era when large amounts of data are generated daily in various fields, the biomedical field among others, linguistic resources can be exploited for various tasks of Natural Language Processing. Moreover, increasing number of biomedical documents are available in languages other than English. To be able to extract information from natural language free text resources, methods and tools are needed for a variety of languages. This paper presents the creation of the MoNERo corpus, a gold standard biomedical corpus for Romanian, annotated with both part of speech tags and named entities. MoNERo comprises 154,825 morphologically annotated tokens and 23,188 entity annotations belonging to four entity semantic groups corresponding to UMLS Semantic Groups.
%R 10.18653/v1/W19-5008
%U https://aclanthology.org/W19-5008
%U https://doi.org/10.18653/v1/W19-5008
%P 71-79

Markdown (Informal)

[MoNERo: a Biomedical Gold Standard Corpus for the Romanian Language](https://aclanthology.org/W19-5008) (Mitrofan et al., BioNLP 2019)

• MoNERo: a Biomedical Gold Standard Corpus for the Romanian Language (Mitrofan et al., BioNLP 2019)

ACL

• Maria Mitrofan, Verginica Barbu Mititelu, and Grigorina Mitrofan. 2019. MoNERo: a Biomedical Gold Standard Corpus for the Romanian Language. In Proceedings of the 18th BioNLP Workshop and Shared Task, pages 71–79, Florence, Italy. Association for Computational Linguistics.