Abstract

The paper presents a fully documented case study of how high-quality data combined with evaluators’ expertise can be utilised for conducting basic NLP experiments in the realm of low-resource languages such as local varieties of Colloquial Arabic, and how the Arabic Bible, hitherto underutilised in NLP, can serve as an evaluation tool. Our experiments on one of the rural Palestinian Arabic dialects of al-Khalīl / Hebron illustrate two points. On the one hand, popular models are clearly limited in their ability to produce outputs of a high level of dialectal specificity (here: rural area surrounding a major urban centre). On the other hand, they are capable to generate accurate translations from such dialects into Modern Standard Arabic. Thus, the models appear better at understanding dialects than at producing dialects.