• Natalia Loukachevitch
  • P. I. Braslavski
  • V. Ivanov
  • Tatiana Batura
  • Suresh Manandhar
  • Artem O. Shelmanov
  • E. V. Tutubalina
In this paper, we describe entity linking annotation over nested named entities in the recently released Russian NEREL dataset for information extraction. The NEREL collection (Loukachevitch et al., 2021) is currently the largest Russian dataset annotated with entities and relations. The paper describes the main design principles behind NEREL's entity linking annotation, provides its statistics, and reports evaluation results for several entity linking baselines. To date, 38,152 entity mentions in 933 documents are linked to Wikidata. The NEREL dataset is publicly available: https://github.com/nerel-ds/NEREL.
Original languageEnglish
Title of host publicationProceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022)
EditorsN. Calzolari, F. Bechet, K. Choukri
PublisherEuropean Language Resources Association (ELRA)
Pages4458-4466
Number of pages9
ISBN (Print)979-109554672-6
Publication statusPublished - 2022

Publication series

NameProceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022)

    ASJC Scopus subject areas

  • Education
  • Linguistics and Language

    WoS ResearchAreas Categories

  • Computer Science, Interdisciplinary Applications

ID: 33232197