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        <title>The risk of sub-optimal use of Open Source NLP Software: UKB is inadvertently state-of-the-art in knowledge-based WSD</title>
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        <namePart type="given">Eneko</namePart>
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            <title>Proceedings of Workshop for NLP Open Source Software (NLP-OSS)</title>
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            <namePart type="given">Eunjeong</namePart>
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            <namePart type="family">Park</namePart>
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        <name type="personal">
            <namePart type="given">Masato</namePart>
            <namePart type="family">Hagiwara</namePart>
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        <name type="personal">
            <namePart type="given">Dmitrijs</namePart>
            <namePart type="family">Milajevs</namePart>
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        <name type="personal">
            <namePart type="given">Liling</namePart>
            <namePart type="family">Tan</namePart>
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    <abstract>UKB is an open source collection of programs for performing, among other tasks, Knowledge-Based Word Sense Disambiguation (WSD). Since it was released in 2009 it has been often used out-of-the-box in sub-optimal settings. We show that nine years later it is the state-of-the-art on knowledge-based WSD. This case shows the pitfalls of releasing open source NLP software without optimal default settings and precise instructions for reproducibility.</abstract>
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        <date>2018-07</date>
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%0 Conference Proceedings
%T The risk of sub-optimal use of Open Source NLP Software: UKB is inadvertently state-of-the-art in knowledge-based WSD
%A Agirre, Eneko
%A López de Lacalle, Oier
%A Soroa, Aitor
%Y Park, Eunjeong L.
%Y Hagiwara, Masato
%Y Milajevs, Dmitrijs
%Y Tan, Liling
%S Proceedings of Workshop for NLP Open Source Software (NLP-OSS)
%D 2018
%8 July
%I Association for Computational Linguistics
%C Melbourne, Australia
%F agirre-etal-2018-risk
%X UKB is an open source collection of programs for performing, among other tasks, Knowledge-Based Word Sense Disambiguation (WSD). Since it was released in 2009 it has been often used out-of-the-box in sub-optimal settings. We show that nine years later it is the state-of-the-art on knowledge-based WSD. This case shows the pitfalls of releasing open source NLP software without optimal default settings and precise instructions for reproducibility.
%R 10.18653/v1/W18-2505
%U https://aclanthology.org/W18-2505/
%U https://doi.org/10.18653/v1/W18-2505
%P 29-33

Markdown (Informal)

[The risk of sub-optimal use of Open Source NLP Software: UKB is inadvertently state-of-the-art in knowledge-based WSD](https://aclanthology.org/W18-2505/) (Agirre et al., NLPOSS 2018)

• The risk of sub-optimal use of Open Source NLP Software: UKB is inadvertently state-of-the-art in knowledge-based WSD (Agirre et al., NLPOSS 2018)

ACL

• Eneko Agirre, Oier López de Lacalle, and Aitor Soroa. 2018. The risk of sub-optimal use of Open Source NLP Software: UKB is inadvertently state-of-the-art in knowledge-based WSD. In Proceedings of Workshop for NLP Open Source Software (NLP-OSS), pages 29–33, Melbourne, Australia. Association for Computational Linguistics.