Abstract
Despite the noticeable progress that we recently witnessed in Arabic pre-trained language models (PLMs), the linguistic knowledge captured by these models remains unclear. In this paper, we conducted a study to evaluate available Arabic PLMs in terms of their linguistic knowledge. BERT-based language models (LMs) are evaluated using Minimum Pairs (MP), where each pair represents a grammatical sentence and its contradictory counterpart. MPs isolate specific linguistic knowledge to test the model’s sensitivity in understanding a specific linguistic phenomenon. We cover nine major Arabic phenomena: Verbal sentences, Nominal sentences, Adjective Modification, and Idafa construction. The experiments compared the results of fifteen Arabic BERT-based PLMs. Overall, among all tested models, CAMeL-CA outperformed the other PLMs by achieving the highest overall accuracy.- Anthology ID:
- 2022.wanlp-1.17
- Volume:
- Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Editors:
- Houda Bouamor, Hend Al-Khalifa, Kareem Darwish, Owen Rambow, Fethi Bougares, Ahmed Abdelali, Nadi Tomeh, Salam Khalifa, Wajdi Zaghouani
- Venue:
- WANLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 185–193
- Language:
- URL:
- https://aclanthology.org/2022.wanlp-1.17
- DOI:
- 10.18653/v1/2022.wanlp-1.17
- Cite (ACL):
- Wafa Abdullah Alrajhi, Hend Al-Khalifa, and Abdulmalik AlSalman. 2022. Assessing the Linguistic Knowledge in Arabic Pre-trained Language Models Using Minimal Pairs. In Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP), pages 185–193, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- Assessing the Linguistic Knowledge in Arabic Pre-trained Language Models Using Minimal Pairs (Alrajhi et al., WANLP 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2022.wanlp-1.17.pdf