camel_tools

Why we included this project

Arabic text processing is genuinely hard to get right, and most teams end up wiring together several libraries just to cover the basics. camel_tools bundles the pipeline into one Python package: tokenization, morphological analysis and disambiguation, part-of-speech tagging, stemming, named-entity recognition, sentiment analysis, and dialect identification. The morphology work is where it earns its keep, since Arabic word forms are notoriously ambiguous and that is exactly where other tools tend to fall short. Pretrained models and datasets install with a single command, so you get working components rather than research code you would have to train yourself. It is built by the CAMeL Lab at NYU Abu Dhabi, so the linguistic decisions are documented and defensible, and the MIT license makes it safe to embed in commercial products.