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A Computational Model for Resolving Arabic Anaphora using Linguistic Criteria


  • FTSM, University Kebangsaan Malaysia, 43600 Bangi,, Malaysia
  • FTSM, University Kebangsaan Malaysia, 43600 Bangi,


Anaphora resolution is seen to be a very challenging and complex problem in the NLP. A majority of the NLP applications used for question answering, information extraction, and text summarisation, need a proper resolution and identification of the anaphora. Despite the fact that several authors have published studies for anaphora resolution in many European languages, including English, very few studies have been published for anaphora resolution in the Arabic language. In our study, we have proposed a novel model for the Arabic pronominal anaphora resolution. Our model contains several steps. In the first step, we have identified the pronouns and removed the non-anaphoric pronouns. In the second step, we have identified a list of the candidates from the context around the anaphora. Lastly, we selected the most probable candidates for every identified anaphoric pronoun. In our study, we have determined the proper rules which can be used for this task. The different linguistic rules depend on the morphological, lexical, heuristic, syntactic, and the positional constraints. We have assessed the performance of our proposed model using the Quran corpus, which was annotated with the pronominal anaphora. Our experimental results indicated that our proposed model was able to yield good results and could also choose the appropriate antecedents with 84.43% accuracy.


Anaphora Resolution; Linguistic Rule, Rule Based Method

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  • Houfeng W, On Anaphora Resolution within Chinese Text, Applied Linguistics. 2004; 52(4):113−19.
  • Holen G. Automatic Anaphora Resolution for Norwegian, Springer, Lecture Notes in Computer Science. Berlin, Germany; 2007. 4410.
  • Dutta K, Prakash N, Kaushik S. Resolving Pronominal Anaphora in Hindi using Hobbs’ Algorithm, Web Journal of Formal Computation and Cognitive Linguistics. 2008; 1(10).
  • Ali R, Khan M, Rabbi I. Strong Personal Anaphora Resolution in Pashto Discourse. Proceedings of EEE ICET 3rd International Conference on Emerging Technologies, Islamabad, Pakistan; 2007.
  • Soon W, Ng H, Lim D. A Machine Learning Approach to Coreference Resolution of Noun Phrase, Computational Linguistics. 2011; 27.
  • Ng V. Cardie C. Improving Machine Learning Approaches to Coreference Resolution. Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics (ACL), Philadelphia, 2002.
  • Jauregi AZ, Sierra B, Uriarte O, Ceberio K, Illarraza A, Goenaga I. A Combination of Classifiers for the Pronominal Anaphora Resolution in Basque, Springer, Lecture Notes in Computer Science, Germany. 2010; 6419:253–60.
  • Abdul-Mageed M. Automatic Detection of Arabic NonAnaphoric Pronouns for Improving Anaphora Resolution, Journal ACM Transactions on Asian Language Information Processing. 2011; 10:1−11.
  • Le M Tran, Nguyen T, Ha Q. Co-Reference Resolution in Vietnamese Documents Based on Support Vector Machines, International Journal of Asian Language Processing IALP.2011; 89−92.
  • Fallahi F, Shamsfard M. Recognizing Anaphora Reference in Persian Sentences, International Journal of Computer Science. 2011; 8:324−29.
  • Tüfekçi P, Kılıçaslan Y. A Computational Model for Resolving Pronominal Anaphora in Turkish using Hobbs Naïve Algorithm, International Journal of Computer, Information Science and Engineerin. 2005; 1(5):1416−20.
  • Khan M, Ali M, Khan M. Treatment of Pronominal Anaphoric Devices in Urdu Discourse. Proceedings of IEEE ICET 2nd International Conference on Emerging Technologies, UET Lahore, Pakistan; 2006.
  • Ali R, Kha M, Ahmad R, Rabbi I. Rule based Personal References Resolution in Pashto Discourse for Better Machine Translation. Proceedings of IEEE ICEE 2nd International Conference on Electrical Engineering; 2008.P. 1−6.
  • Noor N, Aziz M, Noah S, Hamzah M. Anaphora Resolution of Malay Text: Issues and Proposed Solution Model.International Conference on Asian Language Processing IALP; 2011. P. 174−77.
  • Converse S. Resolving Pronominal References in Chinese with the Hobbs Algorithm. Proceedings of SIGHAN workshop on Chinese language processing; 2005. p. 116−22.
  • Hammami S, Sallemi R, Belguith L. A Bayesian Classifier for the Identification of Non-Referential Pronouns in Arabic. Proceedings of the 7th International Conference on Informatics and Systems; 2010 March 28-30. p. 1−6.
  • Hammami S, Belguith L, Hamadou A. Arabic Anaphora Resolution: Corpora Annotation with Coreferential Links, The International Arab Journal of Information Technology.2009; 6:481−89.
  • Albared M, Omar N, Aziz M, Nazri M. Automatic Part of Speech Tagging for Arabic: an Experiment using Bigram Hidden Markov Model. Proceedings of the 5th International Conference, Rough Set and Knowledge Technology, Beijing, China. 2010 October 15-17.
  • Albared M, Omar N, Aziz M. Improving Arabic PartofSpeech Tagging through Morphological Analysis.Proceedings of the Intelligent Information and Database Systems, Daegu, Korea. 2011 April 20-22.
  • Mohammed M, Omar N. Rule based Shallow Parser for Arabic Language, Journal of Computer Science. 2011; 7:1505−14.
  • Hammadi O, Aziz M. Grammatical Relation Extraction in Arabic Language, Journal of Computer Science. 2012; 8:891−98.


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