Abstract
Maltese is a morphologically rich language with a hybrid morphological system which features both concatenative and non-concatenative processes. This paper analyses the impact of this hybridity on the performance of machine learning techniques for morphological labelling and clustering. In particular, we analyse a dataset of morphologically related word clusters to evaluate the difference in results for concatenative and non-concatenative clusters. We also describe research carried out in morphological labelling, with a particular focus on the verb category. Two evaluations were carried out, one using an unseen dataset, and another one using a gold standard dataset which was manually labelled. The gold standard dataset was split into concatenative and non-concatenative to analyse the difference in results between the two morphological systems.- Anthology ID:
- W17-1304
- Volume:
- Proceedings of the Third Arabic Natural Language Processing Workshop
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Editors:
- Nizar Habash, Mona Diab, Kareem Darwish, Wassim El-Hajj, Hend Al-Khalifa, Houda Bouamor, Nadi Tomeh, Mahmoud El-Haj, Wajdi Zaghouani
- Venue:
- WANLP
- SIG:
- SEMITIC
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 25–34
- Language:
- URL:
- https://aclanthology.org/W17-1304
- DOI:
- 10.18653/v1/W17-1304
- Cite (ACL):
- Claudia Borg and Albert Gatt. 2017. Morphological Analysis for the Maltese Language: The challenges of a hybrid system. In Proceedings of the Third Arabic Natural Language Processing Workshop, pages 25–34, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- Morphological Analysis for the Maltese Language: The challenges of a hybrid system (Borg & Gatt, WANLP 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/W17-1304.pdf