Noor Analysis: A Benchmark Dataset for Evaluating Morphological Analysis Engines
Subject Areas : ICTHuda Al-Shohayyeb 1 , Behrooz Minaei 2 , Mohammad Ebrahim Shenassa 3 , Sayyed Ali Hossayni 4
1 - Phd Student
2 -
3 -
4 -
Keywords: Morphology, Arabic Language, Annotation, Dataset, Morphological Analysis,
Abstract :
The Arabic language has a very rich and complex morphology, which is very useful for the analysis of the Arabic language, especially in traditional Arabic texts such as historical and religious texts, and helps in understanding the meaning of the texts. In the morphological data set, the variety of labels and the number of data samples helps to evaluate the morphological methods, in this research, the morphological dataset that we present includes about 22, 3690 words from the book of Sharia alـIslam, which have been labeled by experts, and this dataset is the largest in terms of volume and The variety of labels is superior to other data provided for Arabic morphological analysis. To evaluate the data, we applied the Farasa system to the texts and we report the annotation quality through four evaluation on the Farasa system.
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