New Combined Method to Improve Arabic POS Tagging

Journal: Journal of Autonomous Intelligence DOI: 10.32629/jai.v1i2.30

Mohamed Labidi

LaTICE laboratory, Tunisia


One of the important tasks in Natural language processing is the part of speech tagging. For the Arabic language we have a lot of works but their performances do not rise to the required level, due to the complexity of the task and the Arabic language characteristics. In this work we study a combination between twodifferent approaches for Arabic POS-Taggers. The first one isa maximum entropy-based one, and the second is a statistical/rule-based one. Furthermore, we add a knowledge-based method to annotate Arabic particles. Our idea improves the accuracy rate. We passed from almost 85% to almost 90% using our combined method, which seem promoter.


POS-Tagger, Natural language processing, Arabic language


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Copyright © 2019 Mohamed Labidi

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