Abstract

This paper presents a simple parser to parse Arabic sentences. The aim of this parser is to check whether the syntax of an Arabic sentence is grammatically correct or not by constructing new efficient Context-Free Grammar that makes Top-Down technique much valuable. A set of experiments were ran on a dataset contains 150 Arabic sentence. The system achieved an average accuracy of 95%.

References

• Ahmad T. Al-Taani, Mohammed M. Msallam, and Sana A. Wedian. A top-down chart parser for analyzing arabic sentences. Int. Arab J. Inf. Technol. , 9(2):109–116, 2012.
• Shihadeh Alqrainy. A Morphological-Syntactical Analysis Approach For Arabic Textual Tagging. PhD thesis, De Montfort University - UK, 2008.
• L. Bala, S. Ishwar, and S. Kumar. Context free grammar for natural language constructs - an implementation for venpa class of tamil poetry, 2003.
• Bilal M. Bataineh and Emad A. Bataineh. An efficient recursive transition network parser for arabic language. In Proceedings of the World Congress on Engineering 2009 Vol II, WCE '09, July 1 - 3, 2009, London, U. K. , Lecture Notes in Engineering and Computer Science, pages 1307– 1311. International Association of Engineers, Newswood Limited, 2009.
• David Chiang, Mona Diab, Nizar Habash, Owen Rambow, and Safiullah Shareef. Parsing arabic dialects. In Final Report, 2005 JHU Summer Workshop, 2005.
• J. Earley. An efficient context-free parsing algorithm. Communications of the ACM (CACM), 13(2), February 1970.
• Antony P J, Nandini. J. Warrier, and Dr. Soman K P. Article: penn treebank-based syntactic parsers for south dravidian languages using a machine learning approach. International Journal of Computer Applications, 7(8):14–21, October 2010. Published By Foundation of Computer Science.
• Edward Loper and Steven Bird. Nltk: The natural language toolkit. In Proceedings of the ACL Workshop on Effective Tools and Methodologies for Teaching Natural Language Processing and Computational Linguistics, 2002.
• M. Mccord and V. Cavalli-Sforza. An arabic slot grammar parser. In Workshop on Computational Approaches to Semitic Languages: Common Issues and Resources, 2007.
• Hasan Muaidi. Extraction of Arabic word roots: An Approach Based on Computational Model and Multi- Backpropagation Neural Networks. PhD thesis, De Montfort University - UK, 2008.
• E. Othman, K. Shaalan, and A. Rafea. A chart parser for analyzing modern standard arabic sentence. In Proceedings of the MT Summit IX Workshop on Machine Translation for Semitic Languages: Issues and Approaches, USA, 2003.
• R. Ouersighni. Towards developing a robust large-scale parser for arabic sentences. In Proceedings of the International Arab Conference on Information Technology, 2008.
• D. Rao, P. Bhattacharyya, and R. Mamidi. Natural language generation for english to hindi human aided machine translation. In International Conference on Knowledge Based Computer Systems (KBCS 1998), Mumbai, December, 1998.
• Recursive Descent Parser. http://nltk. googlecode. com/svn/trunk/doc/api/ nltk. app. rdparserapp-module. html, 2012.
• B. Sagar, G. Shobha, and R. Kumar. Context-free grammar analysis for simple kannada sentences. In International Conference [ACCTA-2010], August, 2010.
• K. Shaalan, A. Farouk, and A. Rafea. Towards an arabic parser for modern scientific text. In Proceeding of the 2nd Conference on Language Engineering, Egyptian Society of Language Engineering, Egypt, 2010.
• Lee Spector, Kyle Harrington, and Thomas Helmuth. Tagbased modularity in tree-based genetic programming. In GECCO '12: Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference, pages 815–822, Philadelphia, Pennsylvania, USA, 7-11 July 2012.
• Lamia Tounsi, Mohammed Attia, and Josef van Genabith. Parsing arabic using treebank-based lfg resources. In Proceedings of the LFG Conference, 2009.
• Transparent Language. http://www. transparent. com/.