Tag

#ArabicNLP

Arabic natural language processing is a field where hard linguistic problems meet scarce resources and high stakes. These posts track the work of tokenizing a morphology-rich language, building embeddings that respect dialect rather than collapsing it into a fictional standard, and training models on corpora that are small, noisy, and politically loaded. The posts here are not tutorials. They are field notes on why Arabic NLP keeps underperforming English on standard benchmarks, why that underperformance is often a data problem dressed up as a science problem, and why the researchers grinding away on dialect-aware models and community-built datasets deserve more attention than they get. The broader lesson is about who language technology is built for, and what gets possible when the answer changes.