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Entity Linking over Nested Named Entities for Russian. / Loukachevitch, Natalia; Braslavski, Pavel; Ivanov, Vladimir и др.

Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022). European Language Resources Association (ELRA), 2022. стр. 4458-4466.

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование

Harvard

Loukachevitch, N, Braslavski, P, Ivanov, V, Батура, ТВ, Manandhar, S, Shelmanov, A & Tutubalina, EV 2022, Entity Linking over Nested Named Entities for Russian. в Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022). European Language Resources Association (ELRA), стр. 4458-4466, 13th International Conference on Language Resources and Evaluation Conference, Marseille, Франция, 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. в Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022) (стр. 4458-4466). European Language Resources Association (ELRA).

Vancouver

Loukachevitch N, Braslavski P, Ivanov V, Батура ТВ, Manandhar S, Shelmanov A и др. Entity Linking over Nested Named Entities for Russian. в Proceedings of the 13th Conference on Language Resources and Evaluation (LREC 2022). European Language Resources Association (ELRA). 2022. стр. 4458-4466

Author

Loukachevitch, Natalia ; Braslavski, Pavel ; Ivanov, Vladimir и др. / 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. стр. 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 -

ID: 46056546