TY - GEN
T1 - NADI 2022
T2 - 7th Arabic Natural Language Processing Workshop, WANLP 2022 held with EMNLP 2022
AU - Abdul-Mageed, Muhammad
AU - Zhang, Chiyu
AU - Elmadany, Abdel Rahim
AU - Bouamor, Houda
AU - Habash, Nizar
N1 - Publisher Copyright:
© 2022 Association for Computational Linguistics.
PY - 2022
Y1 - 2022
N2 - We describe the findings of the third Nuanced Arabic Dialect Identification Shared Task (NADI 2022). NADI aims at advancing state-of-the-art Arabic NLP, including Arabic dialects. It does so by affording diverse datasets and modeling opportunities in a standardized context where meaningful comparisons between models and approaches are possible. NADI 2022 targeted both dialect identification (Subtask 1) and dialectal sentiment analysis (Subtask 2) at the country level. A total of 41 unique teams registered for the shared task, of whom 21 teams have participated (with 105 valid submissions). Among these, 19 teams participated in Subtask 1, and 10 participated in Subtask 2. The winning team achieved F1=27.06 on Subtask 1 and F1=75.16 on Subtask 2, reflecting that both subtasks remain challenging and motivating future work in this area. We describe the methods employed by the participating teams and offer an outlook for NADI.
AB - We describe the findings of the third Nuanced Arabic Dialect Identification Shared Task (NADI 2022). NADI aims at advancing state-of-the-art Arabic NLP, including Arabic dialects. It does so by affording diverse datasets and modeling opportunities in a standardized context where meaningful comparisons between models and approaches are possible. NADI 2022 targeted both dialect identification (Subtask 1) and dialectal sentiment analysis (Subtask 2) at the country level. A total of 41 unique teams registered for the shared task, of whom 21 teams have participated (with 105 valid submissions). Among these, 19 teams participated in Subtask 1, and 10 participated in Subtask 2. The winning team achieved F1=27.06 on Subtask 1 and F1=75.16 on Subtask 2, reflecting that both subtasks remain challenging and motivating future work in this area. We describe the methods employed by the participating teams and offer an outlook for NADI.
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M3 - Conference contribution
AN - SCOPUS:85144251341
T3 - WANLP 2022 - 7th Arabic Natural Language Processing - Proceedings of the Workshop
SP - 85
EP - 97
BT - WANLP 2022 - 7th Arabic Natural Language Processing - Proceedings of the Workshop
PB - Association for Computational Linguistics (ACL)
Y2 - 8 December 2022
ER -