Abstract
In this paper, we present a vision for a comprehensive unified lexical resource for computational processing of Arabic with as many of its variants as possible. We will review the current state of the art for three existing resources and then propose a method to link them in addition to augment them in a manner that would render them even more useful for natural language processing whether targeting enabling technologies such as part of speech tagging or parsing, or applications such as Machine Translation, or Information Extraction. The unified lexical resource, Tharawat, meaning treasures, is an extension of our core unique resource Tharwa, which is a three way computational lexicon for Dialectal Arabic, Modern Standard Arabic, and English lemma correspondents. Tharawat will incorporate two other current resources namely SANA, our Arabic Sentiment Lexicon, and MuSTalAHAt, our Multiword Expression (MWE) version of Tharwa but instead of listing lemmas and their correspondents, it lists MWE and their correspondents. Moreover, we present a roadmap for incorporating links for Tharawat to existing English resources and corpora leveraging advanced machine learning techniques and crowd sourcing methods. Such resources are at the core of NLP technologies. Specifically, we believe that such a resource could lead to significant leaps and strides for Arabic NLP. Possessing them for a language such as Arabic could be quite impactful for the development of advanced scientific material and hence lead to an Arabic scientific and economic revolution.
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Diab, M. (2015). Tharawat: A Vision for a Comprehensive Resource for Arabic Computational Processing. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2015. Lecture Notes in Computer Science(), vol 9041. Springer, Cham. https://doi.org/10.1007/978-3-319-18111-0_7
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DOI: https://doi.org/10.1007/978-3-319-18111-0_7
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