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Leveraging multilingual descriptions for link prediction: Initial experiments

Gesese, G. A. ORCID iD icon 1; Alam, M. 1; Hoppe, F. ORCID iD icon 1; Sack, H. 1
1 Karlsruher Institut für Technologie (KIT)


In most Knowledge Graphs (KGs), textual descriptions ofentities are provided in multiple natural languages. Additional informa-tion that is not explicitly represented in the structured part of the KGmight be available in these textual descriptions. Link prediction modelswhich make use of entity descriptions usually consider only one language.However, descriptions given in multiple languages may provide comple-mentary information which should be taken into consideration for thetasks such as link prediction. In this poster paper, the benefits of mul-tilingual embeddings for incorporating multilingual entity descriptionsinto the task of link prediction in KGs are investigated

Verlagsausgabe §
DOI: 10.5445/IR/1000127038
Veröffentlicht am 27.12.2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Angewandte Informatik und Formale Beschreibungsverfahren (AIFB)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 1613-0073
KITopen-ID: 1000127038
Erschienen in CEUR workshop proceedings
Verlag RWTH Aachen
Band 2721
Seiten 84-88
Bemerkung zur Veröffentlichung 19th International Semantic Web Conference on Demos and Industry Tracks: From Novel Ideas to Industrial Practice, ISWC-Posters 2020; Virtual, Online; ; 1 November 2020 through 6 November 2020
Nachgewiesen in Scopus
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