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    <titleInfo>
        <title>Who mentions whom? Recognizing political actors in proceedings</title>
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    <name type="personal">
        <namePart type="given">Lennart</namePart>
        <namePart type="family">Kerkvliet</namePart>
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    <name type="personal">
        <namePart type="given">Maarten</namePart>
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            <title>Proceedings of the Second ParlaCLARIN Workshop</title>
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        <name type="personal">
            <namePart type="given">Darja</namePart>
            <namePart type="family">Fišer</namePart>
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        <name type="personal">
            <namePart type="given">Maria</namePart>
            <namePart type="family">Eskevich</namePart>
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            <namePart type="given">Franciska</namePart>
            <namePart type="family">de Jong</namePart>
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            <publisher>European Language Resources Association</publisher>
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    <abstract>We show that it is straightforward to train a state of the art named entity tagger (spaCy) to recognize political actors in Dutch parliamentary proceedings with high accuracy. The tagger was trained on 3.4K manually labeled examples, which were created in a modest 2.5 days work. This resource is made available on github. Besides proper nouns of persons and political parties, the tagger can recognize quite complex definite descriptions referring to cabinet ministers, ministries, and parliamentary committees. We also provide a demo search engine which employs the tagged entities in its SERP and result summaries.</abstract>
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%0 Conference Proceedings
%T Who mentions whom? Recognizing political actors in proceedings
%A Kerkvliet, Lennart
%A Kamps, Jaap
%A Marx, Maarten
%Y Fišer, Darja
%Y Eskevich, Maria
%Y de Jong, Franciska
%S Proceedings of the Second ParlaCLARIN Workshop
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-47-4
%G English
%F kerkvliet-etal-2020-mentions
%X We show that it is straightforward to train a state of the art named entity tagger (spaCy) to recognize political actors in Dutch parliamentary proceedings with high accuracy. The tagger was trained on 3.4K manually labeled examples, which were created in a modest 2.5 days work. This resource is made available on github. Besides proper nouns of persons and political parties, the tagger can recognize quite complex definite descriptions referring to cabinet ministers, ministries, and parliamentary committees. We also provide a demo search engine which employs the tagged entities in its SERP and result summaries.
%U https://aclanthology.org/2020.parlaclarin-1.7
%P 35-39

Markdown (Informal)

[Who mentions whom? Recognizing political actors in proceedings](https://aclanthology.org/2020.parlaclarin-1.7) (Kerkvliet et al., ParlaCLARIN 2020)

• Who mentions whom? Recognizing political actors in proceedings (Kerkvliet et al., ParlaCLARIN 2020)

ACL

• Lennart Kerkvliet, Jaap Kamps, and Maarten Marx. 2020. Who mentions whom? Recognizing political actors in proceedings. In Proceedings of the Second ParlaCLARIN Workshop, pages 35–39, Marseille, France. European Language Resources Association.