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DBLPLink: An Entity Linker for the DBLP Scholarly Knowledge Graph

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungBegutachtung

Abstract

In this work, we present a web application named DBLPLink, which performs entity linking over the DBLP scholarly knowledge graph. DBLPLink uses text-to-text pre-trained language models, such as T5, to produce entity label spans from an input text question. Entity candidates are fetched from a database based on the labels, and an entity re-ranker sorts them based on entity embeddings, such as TransE, DistMult and ComplEx. The results are displayed so that users may compare and contrast the results between T5-small, T5-base and the different KG embeddings used. The demo can be accessed at https://ltdemos.informatik.uni-hamburg.de/dblplink/. Code and data shall be made available at https://github.com/uhh-lt/dblplink.

OriginalspracheEnglisch
TitelISWC-Posters-Demos-Industry 2023 : Proceedings of the ISWC 2023 Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice ISWC 2023
Redakteure/-innenIrini Fundulaki, Kouji Kozaki, Daniel Garijo, Jose Manuel Gomez-Perez
Seitenumfang5
Band3632
Herausgeber (Verlag)Sun Site Central Europe (RWTH Aachen University)
Erscheinungsdatum2023
DOIs
PublikationsstatusErschienen - 2023
Extern publiziertJa
Veranstaltung22nd International Semantic Web Conference: From Novel Ideas to Industrial Practice - Athens, Griechenland
Dauer: 06.11.202310.11.2023
Konferenznummer: 22
https://iswc2023.semanticweb.org/
https://doi.org/10.25798/ycnb-jn48
https://dblp.org/streams/conf/semweb#2023
http://www.wikidata.org/entity/Q119153957

Bibliographische Notiz

Publisher Copyright:
© 2023 Copyright for this paper by its authors.

Fachgebiete und Schlagwörter

  • Informatik
  • Wirtschaftsinformatik

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