Natural Language Processing
Othman, E., K. Shaalan, and A. Rafea,
"A chart parser for analyzing modern standard Arabic sentence",
MT Summit IX Workshop on Machine Translation for Semitic Languages: Issues and Approaches, New Orleans, Louisiana, USA, ACL, pp. 37–44, September, 2003.
AbstractThe parsing of Arabic sentence is a necessary prerequisite for many natural language processing applications such as machine translation and information retrieval. In this paper we report our attempt to develop an efficient chart parser for Analyzing Modern Standard Arabic (MSA) sentence. From a practical point of view, the parser is able to satisfy syntactic constraints reducing parsing ambiguity. Lexical semantic features are also used to disambiguate the sentence structure. We explain also an Arabic morphological analyzer based on ATN technique. Both the Arabic parser and the Arabic morphological analyzer are implemented in Prolog. The linguistic rules were acquired from a set of sentences from MSA sentence in the Agriculture domain.
Shaalan, K.,
"Machine Translation of Arabic Interrogative Sentence into English",
the 8th International conference on Artificial Intelligence Applications, Cairo, Egypt, American University in Cairo, pp. 473–483, 2000.
AbstractThe present work reports our attempt in developing a bi-lingual Machine Translation (MT) tool in the agriculture domain. The work described here is part of an ongoing research to automate the translation of user interfaces of knowledge-based systems. In particular, we describe the translation of Arabic interrogative sentence into English. In Central Laboratory for Agricultural Expert Systems (CLAES), this tool is found to be essential in developing bilingual (Arabic-to-English) expert systems because both the Arabic and the English versions are needed for development and usage purpose. The tool follows the transfer-based MT approach. A major design goal of this tool is that it can be used as a stand-alone tool and can be very well integrated with a general MT system for Arabic sentence. The paper also describes our experience with the developed MT system and reports results of its application on interrogatives from real agricultural expert systems.
Shaalan, K., A. Farouk, and A. Rafea,
"Towards An Arabic Parser for Modern Scientific Text",
the International Conference on Artificial Intelligence for Decision , Control and Automation in Engineering and Industrial Applications (ACIDCA'2000), Monastir, Tunisia, pp. 228–235, mar, 2000.
AbstractThe present work reports our attempt in developing an Arabic Parser for modern scientific text. The parser is written in Definite Clause Grammar (DCG) and is targeted to be part of a machine translation system. The developing of the parser was a two-step process. In the first step, we acquired the rules that constitute a grammar for Arabic that gives a precise account of what it is for a sentence to be grammatical. The grammar covers a text from the domain of the agricultural extension documents. The second step was to implement the parser that assigns grammatical structure onto input sentence. Experiment on real extension document was performed. The paper will also describe our experience with the developed parser and results of its application on a real agricultural extension document.
Shaalan, K.,
"Extending Prolog for Better Natural Language Analysis",
1st Conference on Language Engineering, Cairo, Egypt, Ain Shams University, pp. 225–236, March, 1998.
AbstractProlog supports natural language parsing with a clean semantics and additional constructs such as definite clause grammars (DCGs). While it provides excellent computational support, we claim it does not provide good notation that increases the readability and maintainability of natural language analysis programming. In this paper we explore an alternative solution: a general notational extension to Prolog programs that provides for concise expression of definitions. This notational extension results in a powerful and convenient logic programming language that fits into natural language analysis programming. Programs translate to Prolog in a way similar to DCGs. That is to say, they have a specific syntax and can be loaded and expanded to Prolog code. This expansion is transparent to the user. To demonstrate the language capabilities, we present an example for an Arabic morphological analyzer.
Rafea, A., and K. Shaalan,
"Lexical Analysis of Inflected Arabic words using Exhaustive Search of an Augmented Transition Network",
Software Practice and Experience, vol. 23, issue 6, no. 6, New York, NY, USA, John Wiley & Sons, Inc., pp. 567–588, 1993.
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