has released Maknuune, a large and open lexicon dedicated to documenting the Palestinian Arabic dialect through a comprehensive methodology.
CAMeL Lab, a research and education lab focusing on artificial intelligence, natural language processing, computational linguistics, and data science, at NYUAD developed the lexicon.
Conceptualised and spearheaded by PhD Student of Linguistics at the University of Oxford Shahd Dibas, the aspiring project was co-led by NYU Abu Dhabi’s Nizar Habash, a computer scientist specialising in computational linguistics. The lexicon is an open-source downloadable resource that encourages both experts and passionate learners to collaboratively lay their linguistic knowledge of the Palestinian Arabic dialect.
The giant database of Maknuune contains over 36,000 entries including phrases and collocations from Standard Arabic in line with the Palestinian Arabic dialect, as well as insights on pronunciation, grammar, usage, synonyms, cultural references, and English translations.
Dibas said, “All of the people involved volunteered their time. I am grateful to the CAMeL Lab for providing their linguistics and computational expertise and adopting this effort. Maknuune has already received global praise from internationally acclaimed scholars, authors, and linguists. We are very excited to be sharing this more broadly with everyone, particularly in light of the upcoming International Mother Language Day.”
Habash commented, “Maknuune is an important milestone towards fulfilling CAMeL Lab’s goals of supporting research on the Arabic language broadly defined as Standard and dialectal variants. In designing Maknuune, we wanted to create a resource that can be used by a wide range of scholars and language enthusiasts — from computational linguists who want to develop tools for Arabic language processing to language educators who want to use it to educate non-native speakers about the rich linguistic heritage of the Arab world, as well as linguists interested in studying Arabic generally and the Palestinian dialect specifically.”