Morphological Segmentation and Part of Speech Tagging for Religious Arabic
نویسنده
چکیده
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.
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