@inproceedings{piskorski-etal-2021-slav,
title = "Slav-{NER}: the 3rd Cross-lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across {S}lavic Languages",
author = "Piskorski, Jakub and
Babych, Bogdan and
Kancheva, Zara and
Kanishcheva, Olga and
Lebedeva, Maria and
Marci{\'n}czuk, Micha{\l} and
Nakov, Preslav and
Osenova, Petya and
Pivovarova, Lidia and
Pollak, Senja and
P{\v{r}}ib{\'a}{\v{n}}, Pavel and
Radev, Ivaylo and
Robnik-Sikonja, Marko and
Starko, Vasyl and
Steinberger, Josef and
Yangarber, Roman",
editor = "Babych, Bogdan and
Kanishcheva, Olga and
Nakov, Preslav and
Piskorski, Jakub and
Pivovarova, Lidia and
Starko, Vasyl and
Steinberger, Josef and
Yangarber, Roman and
Marci{\'n}czuk, Micha{\l} and
Pollak, Senja and
P{\v{r}}ib{\'a}{\v{n}}, Pavel and
Robnik-{\v{S}}ikonja, Marko",
booktitle = "Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing",
month = apr,
year = "2021",
address = "Kiyv, Ukraine",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.bsnlp-1.15",
pages = "122--133",
abstract = "This paper describes Slav-NER: the 3rd Multilingual Named Entity Challenge in Slavic languages. The tasks involve recognizing mentions of named entities in Web documents, normalization of the names, and cross-lingual linking. The Challenge covers six languages and five entity types, and is organized as part of the 8th Balto-Slavic Natural Language Processing Workshop, co-located with the EACL 2021 Conference. Ten teams participated in the competition. Performance for the named entity recognition task reached 90{\%} F-measure, much higher than reported in the first edition of the Challenge. Seven teams covered all six languages, and five teams participated in the cross-lingual entity linking task. Detailed valuation information is available on the shared task web page.",
}
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<abstract>This paper describes Slav-NER: the 3rd Multilingual Named Entity Challenge in Slavic languages. The tasks involve recognizing mentions of named entities in Web documents, normalization of the names, and cross-lingual linking. The Challenge covers six languages and five entity types, and is organized as part of the 8th Balto-Slavic Natural Language Processing Workshop, co-located with the EACL 2021 Conference. Ten teams participated in the competition. Performance for the named entity recognition task reached 90% F-measure, much higher than reported in the first edition of the Challenge. Seven teams covered all six languages, and five teams participated in the cross-lingual entity linking task. Detailed valuation information is available on the shared task web page.</abstract>
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%0 Conference Proceedings
%T Slav-NER: the 3rd Cross-lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across Slavic Languages
%A Piskorski, Jakub
%A Babych, Bogdan
%A Kancheva, Zara
%A Kanishcheva, Olga
%A Lebedeva, Maria
%A Marcińczuk, Michał
%A Nakov, Preslav
%A Osenova, Petya
%A Pivovarova, Lidia
%A Pollak, Senja
%A Přibáň, Pavel
%A Radev, Ivaylo
%A Robnik-Sikonja, Marko
%A Starko, Vasyl
%A Steinberger, Josef
%A Yangarber, Roman
%Y Babych, Bogdan
%Y Kanishcheva, Olga
%Y Nakov, Preslav
%Y Piskorski, Jakub
%Y Pivovarova, Lidia
%Y Starko, Vasyl
%Y Steinberger, Josef
%Y Yangarber, Roman
%Y Marcińczuk, Michał
%Y Pollak, Senja
%Y Přibáň, Pavel
%Y Robnik-Šikonja, Marko
%S Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing
%D 2021
%8 April
%I Association for Computational Linguistics
%C Kiyv, Ukraine
%F piskorski-etal-2021-slav
%X This paper describes Slav-NER: the 3rd Multilingual Named Entity Challenge in Slavic languages. The tasks involve recognizing mentions of named entities in Web documents, normalization of the names, and cross-lingual linking. The Challenge covers six languages and five entity types, and is organized as part of the 8th Balto-Slavic Natural Language Processing Workshop, co-located with the EACL 2021 Conference. Ten teams participated in the competition. Performance for the named entity recognition task reached 90% F-measure, much higher than reported in the first edition of the Challenge. Seven teams covered all six languages, and five teams participated in the cross-lingual entity linking task. Detailed valuation information is available on the shared task web page.
%U https://aclanthology.org/2021.bsnlp-1.15
%P 122-133
Markdown (Informal)
[Slav-NER: the 3rd Cross-lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across Slavic Languages](https://aclanthology.org/2021.bsnlp-1.15) (Piskorski et al., BSNLP 2021)
ACL
- Jakub Piskorski, Bogdan Babych, Zara Kancheva, Olga Kanishcheva, Maria Lebedeva, Michał Marcińczuk, Preslav Nakov, Petya Osenova, Lidia Pivovarova, Senja Pollak, Pavel Přibáň, Ivaylo Radev, Marko Robnik-Sikonja, Vasyl Starko, Josef Steinberger, and Roman Yangarber. 2021. Slav-NER: the 3rd Cross-lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across Slavic Languages. In Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing, pages 122–133, Kiyv, Ukraine. Association for Computational Linguistics.