Named entity recognition

Detecting semantically ambiguous and complex entities in short and low-context settings (like media titles, products, and groups) in 11 languages (including Spanish) in both monolingual and multi-lingual scenarios.

Publication
Shervin Malmasi, Anjie Fang, Besnik Fetahu, Sudipta Kar, and Oleg Rokhlenko. 2022. SemEval-2022 Task 11: Multilingual Complex Named Entity Recognition (MultiCoNER). In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 1412–1437, Seattle, United States. Association for Computational Linguistics.
Competition
SemEval-2022 Task 11: Multilingual Complex Named Entity Recognition (MultiCoNER)
Language
Spanish
English
NLP topic
(named) entity recognition
Abstract task
Sequence labeling
Dataset
MultiCoNER-ES
Year
2022
Publication link
https://aclanthology.org/2022…
Ranking metric
F1

Task results

System F1
DAMO-NLP 0.8994
USTC-NELSLIP 0.8544
Infrrd.ai 0.7526
MaChAmp 0.7520

If you have published a result better than those on the list, send a message to odesia-comunicacion@lsi.uned.es indicating the result and the DOI of the article, along with a copy of it if it is not published openly.