Entity Linking over Nested Named Entities for Russian

Natalia Loukachevitch, Pavel Braslavski, Vladimir Ivanov, Tatiana Batura, Suresh Manandhar, Artem Shelmanov, Elena Tutubalina


Abstract
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 is currently the largest Russian dataset annotated with entities and relations. It includes 933 news texts with annotation of 29 entity types and 49 relation types. 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.
Anthology ID:
2022.lrec-1.474
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
4458–4466
Language:
URL:
https://aclanthology.org/2022.lrec-1.474
DOI:
Bibkey:
Cite (ACL):
Natalia Loukachevitch, Pavel Braslavski, Vladimir Ivanov, Tatiana Batura, Suresh Manandhar, Artem Shelmanov, and Elena Tutubalina. 2022. Entity Linking over Nested Named Entities for Russian. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 4458–4466, Marseille, France. European Language Resources Association.
Cite (Informal):
Entity Linking over Nested Named Entities for Russian (Loukachevitch et al., LREC 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.lrec-1.474.pdf
Code
 nerel-ds/nerel