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Journal Articles Natural Language Engineering Year : 2022

Generating Arabic TAG for syntax-semantics analysis


Arabic presents many challenges for automatic processing. Although several research studies have addressed some issues, electronic resources for processing Arabic remain relatively rare or not widely available. In this paper, we propose a Tree-adjoining grammar with a syntax-semantic interface. It is applied to the modern standard Arabic, but it can be easily adapted to other languages. This grammar named ArabTAG V2.0 (Arabic Tree Adjoining Grammar) is semi-automatically generated by means of an abstract representation called meta-grammar. To ensure its development, ArabTAG V2.0 benefits from a grammar testing environment that uses a corpus of phenomena. Further experiments were performed to check the coverage of this grammar as well as the syntax-semantic analysis. The results showed that ArabTAG V2.0 can cover the majority of syntactical structures and different linguistic phenomena with a precision rate of 88.76%. Moreover, we were able to semantically analyze sentences and build their semantic representations with a precision rate of about 95.63%.

Dates and versions

hal-03696987 , version 1 (16-06-2022)



Cherifa Ben Khelil, Chiraz Ben Othmane Zribi, Denys Duchier, Yannick Parmentier. Generating Arabic TAG for syntax-semantics analysis. Natural Language Engineering, 2022, ⟨10.1017/S1351324922000109⟩. ⟨hal-03696987⟩
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