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Название: NEREL: A Russian Dataset with Nested Named Entities, Relations and Events
Авторы: Loukachevitch, N.
Artemova, E.
Batura, T.
Braslavski, P.
Denisov, I.
Ivanov, V.
Manandhar, S.
Pugachev, A.
Tutubalina, E.
Дата публикации: 2021
Издатель: Incoma Ltd
INCOMA Ltd. Shoumen, BULGARIA
Библиографическое описание: NEREL: A Russian Dataset with Nested Named Entities, Relations and Events / N. Loukachevitch, E. Artemova, T. Batura et al. — DOI 10.1016/j.softx.2022.100995 // International Conference Recent Advances in Natural Language Processing, RANLP. — 2021. — Vol. — P. 876-885.
Аннотация: In this paper, we present NEREL, a Russian dataset for named entity recognition and relation extraction. NEREL is significantly larger than existing Russian datasets: to date it contains 56K annotated named entities and 39K annotated relations. Its important difference from previous datasets is annotation of nested named entities, as well as relations within nested entities and at the discourse level. NEREL can facilitate development of novel models that can extract relations between nested named entities, as well as relations on both sentence and document levels. NEREL also contains the annotation of events involving named entities and their roles in the events. The NEREL collection is available via https://github.com/nerel-ds/NEREL. © 2021 Incoma Ltd. All rights reserved.
Ключевые слова: NAMED ENTITIES
NAMED ENTITY RECOGNITION
RELATION EXTRACTION
URI: http://elar.urfu.ru/handle/10995/112238
Условия доступа: info:eu-repo/semantics/openAccess
Конференция/семинар: International Conference on Recent Advances in Natural Language Processing: Deep Learning for Natural Language Processing Methods and Applications, RANLP 2021
Дата конференции/семинара: 1 September 2021 through 3 September 2021
Идентификатор SCOPUS: 85123612546
Идентификатор PURE: 29556653
ISSN: 1313-8502
ISBN: 9789544520724
DOI: 10.1016/j.softx.2022.100995
Сведения о поддержке: The project is supported by the Russian Science Foundation, grant # 20-11-20166. The experiments were partially carried out on computational resources of HPC facilities at HSE University. We are grateful to Alexey Yandutov and Igor Rozhkov for providing results of their experiments in named entity recognition and relation extraction.
Карточка проекта РНФ: 20-11-20166
Располагается в коллекциях:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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