Abstract
The domain of reverse dictionaries (RDs), while advancing in languages like English and Chinese, remains underdeveloped for Arabic. This study attempts to explore a data-driven approach to enhance word retrieval processes in Arabic RDs. The research focuses on the ArabicNLP 2024 Shared Task, named KSAA-CAD, which provides a dictionary dataset of 39,214 word-gloss pairs, each with a corresponding target word embedding. The proposed solution aims to surpass the baseline performance by employing SOTA deep learning models and innovative data expansion techniques. The methodology involves enriching the dataset with contextually relevant examples, training a T5 model to align the words to their glosses in the space, and evaluating the results on the shared task metrics. We find that our model is closely aligned with the baseline performance on bertseg and bertmsa targets, however does not perform well on electra target, suggesting the need for further exploration.- Anthology ID:
- 2024.arabicnlp-1.78
- Volume:
- Proceedings of The Second Arabic Natural Language Processing Conference
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Nizar Habash, Houda Bouamor, Ramy Eskander, Nadi Tomeh, Ibrahim Abu Farha, Ahmed Abdelali, Samia Touileb, Injy Hamed, Yaser Onaizan, Bashar Alhafni, Wissam Antoun, Salam Khalifa, Hatem Haddad, Imed Zitouni, Badr AlKhamissi, Rawan Almatham, Khalil Mrini
- Venues:
- ArabicNLP | WS
- SIG:
- SIGARAB
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 704–708
- Language:
- URL:
- https://aclanthology.org/2024.arabicnlp-1.78
- DOI:
- 10.18653/v1/2024.arabicnlp-1.78
- Cite (ACL):
- Mais Alheraki and Souham Meshoul. 2024. Baleegh at KSAA-CAD 2024: Towards Enhancing Arabic Reverse Dictionaries. In Proceedings of The Second Arabic Natural Language Processing Conference, pages 704–708, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- Baleegh at KSAA-CAD 2024: Towards Enhancing Arabic Reverse Dictionaries (Alheraki & Meshoul, ArabicNLP-WS 2024)
- PDF:
- https://preview.aclanthology.org/autopr/2024.arabicnlp-1.78.pdf