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        <title>Wordnet-based Evaluation of Large Distributional Models for Polish</title>
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    <name type="personal">
        <namePart type="given">Maciej</namePart>
        <namePart type="family">Piasecki</namePart>
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    <name type="personal">
        <namePart type="given">Gabriela</namePart>
        <namePart type="family">Czachor</namePart>
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    <name type="personal">
        <namePart type="given">Arkadiusz</namePart>
        <namePart type="family">Janz</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Dominik</namePart>
        <namePart type="family">Kaszewski</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Paweł</namePart>
        <namePart type="family">Kędzia</namePart>
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            <title>Proceedings of the 9th Global Wordnet Conference</title>
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        <name type="personal">
            <namePart type="given">Francis</namePart>
            <namePart type="family">Bond</namePart>
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        <name type="personal">
            <namePart type="given">Piek</namePart>
            <namePart type="family">Vossen</namePart>
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                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
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        <name type="personal">
            <namePart type="given">Christiane</namePart>
            <namePart type="family">Fellbaum</namePart>
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            <publisher>Global Wordnet Association</publisher>
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                <placeTerm type="text">Nanyang Technological University (NTU), Singapore</placeTerm>
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    <abstract>The paper presents construction of large scale test datasets for word embeddings on the basis of a very large wordnet. They were next applied for evaluation of word embedding models and used to assess and compare the usefulness of different word embeddings extracted from a very large corpus of Polish. We analysed also and compared several publicly available models described in literature. In addition, several large word embeddings models built on the basis of a very large Polish corpus are presented.</abstract>
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        <url>https://aclanthology.org/2018.gwc-1.26</url>
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        <date>2018-01</date>
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            <start>229</start>
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%0 Conference Proceedings
%T Wordnet-based Evaluation of Large Distributional Models for Polish
%A Piasecki, Maciej
%A Czachor, Gabriela
%A Janz, Arkadiusz
%A Kaszewski, Dominik
%A Kędzia, Paweł
%Y Bond, Francis
%Y Vossen, Piek
%Y Fellbaum, Christiane
%S Proceedings of the 9th Global Wordnet Conference
%D 2018
%8 January
%I Global Wordnet Association
%C Nanyang Technological University (NTU), Singapore
%F piasecki-etal-2018-wordnet
%X The paper presents construction of large scale test datasets for word embeddings on the basis of a very large wordnet. They were next applied for evaluation of word embedding models and used to assess and compare the usefulness of different word embeddings extracted from a very large corpus of Polish. We analysed also and compared several publicly available models described in literature. In addition, several large word embeddings models built on the basis of a very large Polish corpus are presented.
%U https://aclanthology.org/2018.gwc-1.26
%P 229-238

Markdown (Informal)

[Wordnet-based Evaluation of Large Distributional Models for Polish](https://aclanthology.org/2018.gwc-1.26) (Piasecki et al., GWC 2018)

• Wordnet-based Evaluation of Large Distributional Models for Polish (Piasecki et al., GWC 2018)

ACL

• Maciej Piasecki, Gabriela Czachor, Arkadiusz Janz, Dominik Kaszewski, and Paweł Kędzia. 2018. Wordnet-based Evaluation of Large Distributional Models for Polish. In Proceedings of the 9th Global Wordnet Conference, pages 229–238, Nanyang Technological University (NTU), Singapore. Global Wordnet Association.