DBLPLink: An Entity Linker for the DBLP Scholarly Knowledge Graph

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Authors

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.

Original languageEnglish
Title of host publicationISWC-Posters-Demos-Industry 2023 : Proceedings of the ISWC 2023 Posters, Demos and Industry Tracks: From Novel Ideas to Industrial Practice ISWC 2023
EditorsIrini Fundulaki, Kouji Kozaki, Daniel Garijo, Jose Manuel Gomez-Perez
Number of pages5
Volume3632
PublisherSun Site Central Europe (RWTH Aachen University)
Publication date2023
DOIs
Publication statusPublished - 2023
Externally publishedYes
Event22nd International Semantic Web Conference - ISWC 2023: From Novel Ideas to Industrial Practice - Athens, Greece
Duration: 06.11.202310.11.2023
Conference number: 22

Bibliographical note

Funding Information:
This research is performed as a part of the ARDIAS project, funded by the “Idea and Venture Fund“ research grant by Universität Hamburg, which is part of the Excellence Strategy of the Federal and State Governments. This work has additionally received funding through the German Research Foundation ?DFG) project NFDI4DS ?no. 460234259).

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