Standard
Entity Linking over Nested Named Entities for Russian. / Loukachevitch, Natalia; Braslavski, Pavel; Ivanov, Vladimir et al.
Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022). European Language Resources Association (ELRA), 2022. p. 4458-4466.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Harvard
Loukachevitch, N, Braslavski, P, Ivanov, V, Батура, ТВ, Manandhar, S, Shelmanov, A & Tutubalina, EV 2022,
Entity Linking over Nested Named Entities for Russian. in
Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022). European Language Resources Association (ELRA), pp. 4458-4466, 13th International Conference on Language Resources and Evaluation Conference, Marseille, France,
20.06.2022.
APA
Loukachevitch, N., Braslavski, P., Ivanov, V., Батура, Т. В., Manandhar, S., Shelmanov, A., & Tutubalina, E. V. (2022).
Entity Linking over Nested Named Entities for Russian. In
Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022) (pp. 4458-4466). European Language Resources Association (ELRA).
Vancouver
Loukachevitch N, Braslavski P, Ivanov V, Батура ТВ, Manandhar S, Shelmanov A et al.
Entity Linking over Nested Named Entities for Russian. In Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022). European Language Resources Association (ELRA). 2022. p. 4458-4466
Author
Loukachevitch, Natalia ; Braslavski, Pavel ; Ivanov, Vladimir et al. /
Entity Linking over Nested Named Entities for Russian. Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022). European Language Resources Association (ELRA), 2022. pp. 4458-4466
BibTeX
@inproceedings{d2dbcdd8cf83406994248f61dc9e5dbb,
title = "Entity Linking over Nested Named Entities for Russian",
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 (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. {\textcopyright} European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.",
author = "Natalia Loukachevitch and Pavel Braslavski and Vladimir Ivanov and Батура, {Татьяна Викторовна} and Suresh Manandhar and Artem Shelmanov and Tutubalina, {E. V.}",
note = "The project is supported by the Russian Science Foundation, grant # 20-11-20166.; 13th International Conference on Language Resources and Evaluation Conference, LREC 2022 ; Conference date: 20-06-2022 Through 25-06-2022",
year = "2022",
language = "English",
isbn = "979-109554672-6",
pages = "4458--4466",
booktitle = "Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022)",
publisher = "European Language Resources Association (ELRA)",
}
RIS
TY - GEN
T1 - Entity Linking over Nested Named Entities for Russian
AU - Loukachevitch, Natalia
AU - Braslavski, Pavel
AU - Ivanov, Vladimir
AU - Батура, Татьяна Викторовна
AU - Manandhar, Suresh
AU - Shelmanov, Artem
AU - Tutubalina, E. V.
N1 - Conference code: 13
PY - 2022
Y1 - 2022
N2 - 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. © European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.
AB - 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. © European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.
UR - https://www.scopus.com/inward/record.url?eid=2-s2.0-85140868351&partnerID=40&md5=026c6f30d7a1228592d8e0f96b9d8e92
M3 - Conference contribution
SN - 979-109554672-6
SP - 4458
EP - 4466
BT - Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022)
PB - European Language Resources Association (ELRA)
T2 - 13th International Conference on Language Resources and Evaluation Conference
Y2 - 20 June 2022 through 25 June 2022
ER -
