Conference paper Open Access

Recommendation-Assisted Data Curation for Wikidata

Zangerle, Eva; Müller-Birn, Claudia


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    <subfield code="d">April 24, 2018</subfield>
    <subfield code="a">Wiki Workshop 2018 (held at The Web Conference 2018)</subfield>
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    <subfield code="u">University of Innsbruck</subfield>
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    <subfield code="a">Zangerle, Eva</subfield>
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    <subfield code="a">&lt;p&gt;The Wikidata project provides a structured knowledge base that is curated by bots and humans alike. The quality and completeness of data contained is naturally influenced by the users who enter and maintain the data in the form of items described by statements on the platform. Users who are new to the Wikidata environment and its underlying data model, but are, nonetheless, experts in their fields, are confronted with a steep learning curve when aiming to enter information on Wikidata (e.g. regarding the choice of suitable properties for creating statements). In this work, we propose a recommendation-based annotation platform where users who currently work with or on a text are supported in finding suitable Wikidata entities for data extracted from the underlying text source to ultimately feed this structured information to the Wikidata platform. Such recommendations not only support users in annotating their data according to Wikidata&amp;#39;s terminological knowledge, but also expand the number of references on the Wikidata platform that reveal the origin of existing statements.&lt;/p&gt;</subfield>
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