Arabic Fine-Grained Entity Recognition

Haneen Liqreina, Mustafa Jarrar, Mohammed Khalilia, Ahmed El-Shangiti, Muhammad Abdul-Mageed


Abstract
Traditional NER systems are typically trained to recognize coarse-grained categories of entities, and less attention is given to classifying entities into a hierarchy of fine-grained lower-level sub-types. This article aims to advance Arabic NER with fine-grained entities. We chose to extend Wojood (an open-source Nested Arabic Named Entity Corpus) with sub-types. In particular, four main entity types in Wojood (geopolitical entity (GPE), location (LOC), organization (ORG), and facility (FAC) are extended with 31 sub-types of entities. To do this, we first revised Wojood’s annotations of GPE, LOC, ORG, and FAC to be compatible with the LDC’s ACE guidelines, which yielded 5, 614 changes. Second, all mentions of GPE, LOC, ORG, and FAC (~ 44K) in Wojood are manually annotated with the LDC’s ACE subtypes. This extended version of Wojood is called WojoodFine. To evaluate our annotations, we measured the inter-annotator agreement (IAA) using both Cohen’s Kappa and F1 score, resulting in 0.9861 and 0.9889, respectively. To compute the baselines of WojoodFine, we fine-tune three pre-trained Arabic BERT encoders in three settings: flat NER, nested NER and nested NER with sub-types and achieved F1 score of 0.920, 0.866, and 0.885, respectively. Our corpus and models are open source and available at https://sina.birzeit.edu/wojood/.
Anthology ID:
2023.arabicnlp-1.25
Volume:
Proceedings of ArabicNLP 2023
Month:
December
Year:
2023
Address:
Singapore (Hybrid)
Editors:
Hassan Sawaf, Samhaa El-Beltagy, Wajdi Zaghouani, Walid Magdy, Ahmed Abdelali, Nadi Tomeh, Ibrahim Abu Farha, Nizar Habash, Salam Khalifa, Amr Keleg, Hatem Haddad, Imed Zitouni, Khalil Mrini, Rawan Almatham
Venues:
ArabicNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
310–323
Language:
URL:
https://aclanthology.org/2023.arabicnlp-1.25
DOI:
10.18653/v1/2023.arabicnlp-1.25
Bibkey:
Cite (ACL):
Haneen Liqreina, Mustafa Jarrar, Mohammed Khalilia, Ahmed El-Shangiti, and Muhammad Abdul-Mageed. 2023. Arabic Fine-Grained Entity Recognition. In Proceedings of ArabicNLP 2023, pages 310–323, Singapore (Hybrid). Association for Computational Linguistics.
Cite (Informal):
Arabic Fine-Grained Entity Recognition (Liqreina et al., ArabicNLP-WS 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.arabicnlp-1.25.pdf