Triple Classification for Scholarly Knowledge Graph Completion

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Authors

  • Mohamad Yaser Jaradeh
  • Kuldeep Singh
  • Markus Stocker
  • Sören Auer

Research Organisations

External Research Organisations

  • German National Library of Science and Technology (TIB)
  • Zerotha-Research and Cerence GmbH
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Details

Original languageEnglish
Title of host publicationK-CAP 2021
Subtitle of host publicationProceedings of the 11th Knowledge Capture Conference
Place of PublicationNew York
Pages225-232
Number of pages8
ISBN (electronic)9781450384575
Publication statusPublished - 2 Dec 2021
Event11th ACM International Conference on Knowledge Capture, K-CAP 2021 - Virtual, Online, United States
Duration: 2 Dec 20213 Dec 2021

Abstract

structured information representing knowledge encoded in scientific publications. With the sheer volume of published scientific literature comprising a plethora of inhomogeneous entities and relations to describe scientific concepts, these KGs are inherently incomplete. We present exBERT, a method for leveraging pre-trained transformer language models to perform scholarly knowledge graph completion. We model triples of a knowledge graph as text and perform triple classification (i.e., belongs to KG or not). The evaluation shows that exBERT outperforms other baselines on three scholarly KG completion datasets in the tasks of triple classification, link prediction, and relation prediction. Furthermore, we present two scholarly datasets as resources for the research community, collected from public KGs and online resources.

Keywords

    link prediction, relation prediction, scholarly knowledge graphs, triple classification

ASJC Scopus subject areas

Cite this

Triple Classification for Scholarly Knowledge Graph Completion. / Jaradeh, Mohamad Yaser; Singh, Kuldeep; Stocker, Markus et al.
K-CAP 2021: Proceedings of the 11th Knowledge Capture Conference. New York, 2021. p. 225-232.

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Jaradeh, MY, Singh, K, Stocker, M & Auer, S 2021, Triple Classification for Scholarly Knowledge Graph Completion. in K-CAP 2021: Proceedings of the 11th Knowledge Capture Conference. New York, pp. 225-232, 11th ACM International Conference on Knowledge Capture, K-CAP 2021, Virtual, Online, United States, 2 Dec 2021. https://doi.org/10.1145/3460210.3493582
Jaradeh, M. Y., Singh, K., Stocker, M., & Auer, S. (2021). Triple Classification for Scholarly Knowledge Graph Completion. In K-CAP 2021: Proceedings of the 11th Knowledge Capture Conference (pp. 225-232). https://doi.org/10.1145/3460210.3493582
Jaradeh MY, Singh K, Stocker M, Auer S. Triple Classification for Scholarly Knowledge Graph Completion. In K-CAP 2021: Proceedings of the 11th Knowledge Capture Conference. New York. 2021. p. 225-232 doi: 10.1145/3460210.3493582
Jaradeh, Mohamad Yaser ; Singh, Kuldeep ; Stocker, Markus et al. / Triple Classification for Scholarly Knowledge Graph Completion. K-CAP 2021: Proceedings of the 11th Knowledge Capture Conference. New York, 2021. pp. 225-232
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