Digital morphology of the Albanian language
There has been a growing development of the Albanian Natural Language Processing (NLP) in recent years, but morphological analysis remains a critical and under-resourced area. This article presents a comprehensive overview of the Digital Morphology Software, a core component of the Kulla e shqipes 2.0 platform, which is specifically developed to address the morphological complexity of the Albanian language's structure. Designed to serve both computational linguistics and language pedagogy, the software enables automatic analysis, generation, and classification of Albanian word forms across nouns, verbs, adjectives etc. Built on a rule-based and corpus-informed methodology, the system incorporates grammatical models drawn from authoritative Albanian sources. The formulas of these grammatical models apply structured rules to representative stems, ensuring accurate and scalable paradigm generation. The software is accessible via web, desktop, and mobile platforms, offering a responsive interface, real-time analysis, and interactive features. A standout component is the evaluation module, which allows users to complete paradigms manually and receive instant feedback - transforming the platform into a dynamic learning environment. The software is designed to support educational institutions, researchers, teachers, and learners by providing an interactive framework for mastering Albanian morphology. It also acts as a reliable reference tool for editors, linguists, and NLP developers. As one of the most complete morphological tools for Albanian to date, it offers essential infrastructure for advancing NLP applications, corpus annotation, and standardized language instruction.
Authors
- Anila Çepani (ORCID: https://orcid.org/0000-0002-8400-8987)
- Adelina Çerpja (ORCID: https://orcid.org/0000-0001-5740-7109)
Institutions
- Academy of Sciences of Albania (AL)
- Institute of Linguistics (CN)
- University of Tirana (AL)
Publication Details
- Journal
- Journal of Responsible Technology
- Published
- 2026-01-14
- DOI
- https://doi.org/10.1016/j.jrt.2026.100151
- Primary Topic
- Natural Language Processing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00