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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

A Coreference Resolution Approach using Morphological Features in Arabic

Author 1: Majdi Beseiso
Author 2: Abdulkareem Al-Alwani

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2016.071014

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 10, 2016.

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Abstract: Coreference resolution is considered one of the challenges in natural language processing. It is an important task that includes determining which pronouns are referring to which entities. Most of the earlier approaches for coreference resolution are rule-based or machine learning approaches. However, these types of approaches have many limitations especially with Arabic language. In this paper, a different approach to coreference resolution is presented. The approach uses morphological features and dependency trees instead. It has fivestages, which overcomes the limitations of using annotated datasets for learning or a set of rules. The approach was evaluatedusing our own customized annotated dataset and “AnATAr” dataset. The evaluation show encouraging results with average F1 score of 89%.

Keywords: Coreference resolution; Anaphora; Alternative Approach; Arabic NLP; morphological features

Majdi Beseiso and Abdulkareem Al-Alwani, “A Coreference Resolution Approach using Morphological Features in Arabic” International Journal of Advanced Computer Science and Applications(IJACSA), 7(10), 2016. http://dx.doi.org/10.14569/IJACSA.2016.071014

@article{Beseiso2016,
title = {A Coreference Resolution Approach using Morphological Features in Arabic},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.071014},
url = {http://dx.doi.org/10.14569/IJACSA.2016.071014},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {10},
author = {Majdi Beseiso and Abdulkareem Al-Alwani}
}


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