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NEREL: A Russian Dataset with Nested Named Entities, Relations and Events. / Loukachevitch, Natalia; Artemova, Ekaterina; Batura, Tatiana et al.
International Conference Recent Advances in Natural Language Processing, RANLP 2021: Deep Learning for Natural Language Processing Methods and Applications - Proceedings. ed. / Galia Angelova; Maria Kunilovskaya; Ruslan Mitkov; Ivelina Nikolova-Koleva. Incoma Ltd, 2021. p. 876-885 (International Conference Recent Advances in Natural Language Processing, RANLP).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Harvard
Loukachevitch, N, Artemova, E, Batura, T, Braslavski, P, Denisov, I, Ivanov, V, Manandhar, S, Pugachev, A & Tutubalina, E 2021,
NEREL: A Russian Dataset with Nested Named Entities, Relations and Events. in G Angelova, M Kunilovskaya, R Mitkov & I Nikolova-Koleva (eds),
International Conference Recent Advances in Natural Language Processing, RANLP 2021: Deep Learning for Natural Language Processing Methods and Applications - Proceedings. International Conference Recent Advances in Natural Language Processing, RANLP, Incoma Ltd, pp. 876-885, International Conference on Recent Advances in Natural Language Processing: Deep Learning for Natural Language Processing Methods and Applications, RANLP 2021, Virtual, Online,
01.09.2021.
https://doi.org/10.26615/978-954-452-072-4_100APA
Loukachevitch, N., Artemova, E., Batura, T., Braslavski, P., Denisov, I., Ivanov, V., Manandhar, S., Pugachev, A., & Tutubalina, E. (2021).
NEREL: A Russian Dataset with Nested Named Entities, Relations and Events. In G. Angelova, M. Kunilovskaya, R. Mitkov, & I. Nikolova-Koleva (Eds.),
International Conference Recent Advances in Natural Language Processing, RANLP 2021: Deep Learning for Natural Language Processing Methods and Applications - Proceedings (pp. 876-885). (International Conference Recent Advances in Natural Language Processing, RANLP). Incoma Ltd.
https://doi.org/10.26615/978-954-452-072-4_100Vancouver
Loukachevitch N, Artemova E, Batura T, Braslavski P, Denisov I, Ivanov V et al.
NEREL: A Russian Dataset with Nested Named Entities, Relations and Events. In Angelova G, Kunilovskaya M, Mitkov R, Nikolova-Koleva I, editors, International Conference Recent Advances in Natural Language Processing, RANLP 2021: Deep Learning for Natural Language Processing Methods and Applications - Proceedings. Incoma Ltd. 2021. p. 876-885. (International Conference Recent Advances in Natural Language Processing, RANLP). doi: 10.26615/978-954-452-072-4_100
Author
Loukachevitch, Natalia ; Artemova, Ekaterina ; Batura, Tatiana et al. /
NEREL: A Russian Dataset with Nested Named Entities, Relations and Events. International Conference Recent Advances in Natural Language Processing, RANLP 2021: Deep Learning for Natural Language Processing Methods and Applications - Proceedings. editor / Galia Angelova ; Maria Kunilovskaya ; Ruslan Mitkov ; Ivelina Nikolova-Koleva. Incoma Ltd, 2021. pp. 876-885 (International Conference Recent Advances in Natural Language Processing, RANLP).
BibTeX
@inproceedings{01fb4c8a821a4932888bf44a321f33d4,
title = "NEREL: A Russian Dataset with Nested Named Entities, Relations and Events",
abstract = "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.",
author = "Natalia Loukachevitch and Ekaterina Artemova and Tatiana Batura and Pavel Braslavski and Ilia Denisov and Vladimir Ivanov and Suresh Manandhar and Alexander Pugachev and Elena Tutubalina",
note = "Funding Information: 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. Publisher Copyright: {\textcopyright} 2021 Incoma Ltd. All rights reserved.; International Conference on Recent Advances in Natural Language Processing: Deep Learning for Natural Language Processing Methods and Applications, RANLP 2021 ; Conference date: 01-09-2021 Through 03-09-2021",
year = "2021",
doi = "10.26615/978-954-452-072-4_100",
language = "English",
isbn = "9789544520724",
series = "International Conference Recent Advances in Natural Language Processing, RANLP",
publisher = "Incoma Ltd",
pages = "876--885",
editor = "Galia Angelova and Maria Kunilovskaya and Ruslan Mitkov and Ivelina Nikolova-Koleva",
booktitle = "International Conference Recent Advances in Natural Language Processing, RANLP 2021",
}
RIS
TY - GEN
T1 - NEREL: A Russian Dataset with Nested Named Entities, Relations and Events
AU - Loukachevitch, Natalia
AU - Artemova, Ekaterina
AU - Batura, Tatiana
AU - Braslavski, Pavel
AU - Denisov, Ilia
AU - Ivanov, Vladimir
AU - Manandhar, Suresh
AU - Pugachev, Alexander
AU - Tutubalina, Elena
N1 - Funding Information:
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.
Publisher Copyright:
© 2021 Incoma Ltd. All rights reserved.
PY - 2021
Y1 - 2021
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85123612546&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/e186cd3c-ed20-396f-8830-8b9076864fee/
U2 - 10.26615/978-954-452-072-4_100
DO - 10.26615/978-954-452-072-4_100
M3 - Conference contribution
AN - SCOPUS:85123612546
SN - 9789544520724
T3 - International Conference Recent Advances in Natural Language Processing, RANLP
SP - 876
EP - 885
BT - International Conference Recent Advances in Natural Language Processing, RANLP 2021
A2 - Angelova, Galia
A2 - Kunilovskaya, Maria
A2 - Mitkov, Ruslan
A2 - Nikolova-Koleva, Ivelina
PB - Incoma Ltd
T2 - International Conference on Recent Advances in Natural Language Processing: Deep Learning for Natural Language Processing Methods and Applications, RANLP 2021
Y2 - 1 September 2021 through 3 September 2021
ER -
