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        <title>Litescale: A Lightweight Tool for Best-worst Scaling Annotation</title>
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    <name type="personal">
        <namePart type="given">Valerio</namePart>
        <namePart type="family">Basile</namePart>
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            <title>Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)</title>
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            <namePart type="given">Ruslan</namePart>
            <namePart type="family">Mitkov</namePart>
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            <namePart type="given">Galia</namePart>
            <namePart type="family">Angelova</namePart>
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    <abstract>Best-worst Scaling (BWS) is a methodology for annotation based on comparing and ranking instances, rather than classifying or scoring individual instances. Studies have shown the efficacy of this methodology applied to NLP tasks in terms of a higher quality of the datasets produced by following it. In this system demonstration paper, we present Litescale, a free software library to create and manage BWS annotation tasks. Litescale computes the tuples to annotate, manages the users and the annotation process, and creates the final gold standard. The functionalities of Litescale can be accessed programmatically through a Python module, or via two alternative user interfaces, a textual console-based one and a graphical Web-based one. We further developed and deployed a fully online version of Litescale complete with multi-user support.</abstract>
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        <url>https://aclanthology.org/2021.ranlp-1.15</url>
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%0 Conference Proceedings
%T Litescale: A Lightweight Tool for Best-worst Scaling Annotation
%A Basile, Valerio
%A Cagnazzo, Christian
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)
%D 2021
%8 September
%I INCOMA Ltd.
%C Held Online
%F basile-cagnazzo-2021-litescale
%X Best-worst Scaling (BWS) is a methodology for annotation based on comparing and ranking instances, rather than classifying or scoring individual instances. Studies have shown the efficacy of this methodology applied to NLP tasks in terms of a higher quality of the datasets produced by following it. In this system demonstration paper, we present Litescale, a free software library to create and manage BWS annotation tasks. Litescale computes the tuples to annotate, manages the users and the annotation process, and creates the final gold standard. The functionalities of Litescale can be accessed programmatically through a Python module, or via two alternative user interfaces, a textual console-based one and a graphical Web-based one. We further developed and deployed a fully online version of Litescale complete with multi-user support.
%U https://aclanthology.org/2021.ranlp-1.15
%P 121-127

Markdown (Informal)

[Litescale: A Lightweight Tool for Best-worst Scaling Annotation](https://aclanthology.org/2021.ranlp-1.15) (Basile & Cagnazzo, RANLP 2021)

• Litescale: A Lightweight Tool for Best-worst Scaling Annotation (Basile & Cagnazzo, RANLP 2021)

ACL

• Valerio Basile and Christian Cagnazzo. 2021. Litescale: A Lightweight Tool for Best-worst Scaling Annotation. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021), pages 121–127, Held Online. INCOMA Ltd..