Abstract
The grammar analysis is considered one of the complex tasks in the Natural Language Processing (NLP) field, since it determines the relation between the words in the sentence. This paper proposes a system to automate the grammar analysis of Arabic language sentences (Sentence Grammar Analysis, <ErAb Aljml). The task of Arabic grammar analysis has been divide into three sub-tasks, of determining the grammatical tag, the case, and the sign of each token in the level of the sentence. For the task of Arabic grammar analysis, a dataset has been compiled and a statistical system that assigns an appropriate tag, case and sign has been implemented. The proposed system has been tested and the experiments show that it achieves a 89.74% token accuracy and a 63.56% overall sentence accuracy and it has the potential to be further improved.
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Ibrahim, M.N. (2015). Statistical Arabic Grammar Analyzer. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2015. Lecture Notes in Computer Science(), vol 9041. Springer, Cham. https://doi.org/10.1007/978-3-319-18111-0_15
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DOI: https://doi.org/10.1007/978-3-319-18111-0_15
Publisher Name: Springer, Cham
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