Ambiguity Resolution

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Shaalan, K., M. Magdy, and D. Samy, "Towards Resolving Morphological Ambiguity in Arabic Intelligent Language Tutoring Framework", The seventh international conference on Language Resources and Evaluation (LREC'10) Workshop on Supporting eLearning with Language Resources and Semantic Data, Valletta, Malta, LREC, 2010. Abstractlrec2010elearing_workshop.pdf

Ambiguity is a major issue in any NLP application that occurs when multiple interpretations of the same language phenomenon are produced. Given the complexity of the Arabic morphological system, it is difficult to determine what the intended meaning of the writer is. Moreover, Intelligent Language Tutoring Systems which need to analyze erroneous learner answers, generally, introduce techniques, such as constraints relaxation, that would produce more interpretations than systems designed for processing well-formed input. This paper addresses issues related to the morphological disambiguation of corrected interpretations of erroneous Arabic verbs that were written by beginner to intermediate Second Language Learners. The morphological disambiguation has been developed and effectively evaluated using real test data. It achieved satisfactory results in terms of the recall rate.

Othman, E., K. Shaalan, and A. Rafea, "Towards resolving ambiguity in understanding Arabic sentence", International Conference on Arabic Language Resources and Tools, Cairo, Egypt, NEMLAR, pp. 118–122, sep, 2004. Abstractambiguity_resol_nemlar.pdf

Ambiguity is a major reason why computers do not yet understand natural language. We have made great deal strides towards developing tools for morphological and syntactic analyzers for Arabic in recent years. The absence of diacritics, which represent most vowels, in the written text creates ambiguity which hinders the development of Arabic natural language processing applications. Thus, ambiguity increases the range of possible interpretations of natural language. In this paper, we give a road map of solutions to common ambiguity problems inherent in parsing of Arabic sentence.