@inproceedings{mohamed-2012-morphological,
    title = "Morphological Segmentation and Part of Speech Tagging for Religious {A}rabic",
    author = "Mohamed, Emad",
    editor = "Farghaly, Ali  and
      Oroumchian, Farhad",
    booktitle = "Fourth Workshop on Computational Approaches to Arabic-Script-based Languages",
    month = nov # " 1",
    year = "2012",
    address = "San Diego, California, USA",
    publisher = "Association for Machine Translation in the Americas",
    url = "https://preview.aclanthology.org/fix-sig-urls/2012.amta-caas14.9/",
    pages = "65--71",
    abstract = "We annotate a small corpus of religious Arabic with morphological segmentation boundaries and fine-grained segment-based part of speech tags. Experiments on both segmentation and POS tagging show that the religious corpus-trained segmenter and POS tagger outperform the Arabic Treebak-trained ones although the latter is 21 times as big, which shows the need for building religious Arabic linguistic resources. The small corpus we annotate improves segmentation accuracy by 5{\%} absolute (from 90.84{\%} to 95.70{\%}), and POS tagging by 9{\%} absolute (from 82.22{\%} to 91.26) when using gold standard segmentation, and by 9.6{\%} absolute (from 78.62{\%} to 88.22) when using automatic segmentation."
}