WojoodNER 2024: The Second Arabic Named Entity Recognition Shared Task
This work addresses the problem of fine-grained Arabic NER for the NLP community, but it is incremental as it builds on previous shared tasks.
The paper introduced WojoodNER-2024, the second Arabic Named Entity Recognition shared task, which tackled fine-grained NER with a new dataset and three subtasks, resulting in winning teams achieving F-1 scores of 91% and 92% in flat and nested fine-grained NER, and 73.7% in an open-track subtask.
We present WojoodNER-2024, the second Arabic Named Entity Recognition (NER) Shared Task. In WojoodNER-2024, we focus on fine-grained Arabic NER. We provided participants with a new Arabic fine-grained NER dataset called wojoodfine, annotated with subtypes of entities. WojoodNER-2024 encompassed three subtasks: (i) Closed-Track Flat Fine-Grained NER, (ii) Closed-Track Nested Fine-Grained NER, and (iii) an Open-Track NER for the Israeli War on Gaza. A total of 43 unique teams registered for this shared task. Five teams participated in the Flat Fine-Grained Subtask, among which two teams tackled the Nested Fine-Grained Subtask and one team participated in the Open-Track NER Subtask. The winning teams achieved F-1 scores of 91% and 92% in the Flat Fine-Grained and Nested Fine-Grained Subtasks, respectively. The sole team in the Open-Track Subtask achieved an F-1 score of 73.7%.