Abstract
Problem statement: Grammatical Relation (GR) can be defined as a linguistic relation established by grammar, where linguistic relation is an association among the linguistic forms or constituents. Fundamentally the GR determines grammatical behaviors such as: placement of a word in a clause, verb agreement and the passivity behavior. The GR of Arabic language is a necessary prerequisite for many natural language processing applications, such as machine translation and information retrieval. This study focuses on the GR related problems of Arabic language and addresses the issue with optimum solution. Approach: We had proposed a rule based production method to recognize Grammatical Relations (GRs), as the rule-based approach had been successfully used in developing many natural language processing systems. In order to eradicate the problems of sentence structure recognition, the proposed technique enhances the basic representations of Arabic language such as: Noun Phrase (NP), Verb Phrase (VP), Preposition Phrase (PP) and Adjective Phrase (AP). We had implemented and evaluated the Rule-Based approach that handles chunking and GRs of Arabic sentences. Results: The system was manually tested on 80 Arabic sentences, with the length of each sentence ranging from 3-20 words. The results had yielded the F-score of 83.60%. This outcome proves the viability of this approach for Arabic sentences of GRs extraction. Conclusion: The main achievement of this study is development of Arabic grammatical relation extractions based ob rule-based approaches.
Highlights
Grammatical Relation (GR) can be defined as a linguistic relation established by grammar, where linguistic relation is an association among the linguistic forms or constituents
Ahmed (1999) has solved the parser Arabic language using the Rule-based approach and has achieved 77% as highest accuracy
Translation (MT), Index Term Generation (ITG), In order to evaluate the accuracy of the proposed Arab-GR system, the results of system had been
Summary
Grammatical Relation (GR) can be defined as a linguistic relation established by grammar, where linguistic relation is an association among the linguistic forms or constituents. The GR of Arabic language is a necessary prerequisite for many natural language processing applications such as machine translation and information retrieval. Every language has its own set of grammars that makes them unique Diab et al (2004; 2007) and Diab (2009). The serious case of ambiguity arises when they have to be dealt with computers, in terms of translation or information retrieval. The positions of subject, verb and object in every language are the biggest challenge in the information or translation task. The NLP applications fall under the following categories: Information Retrieval (IR), Information Extraction (IE), Question-Answering (QA), Summarization, Machine Translation (MT) and Dialogue Systems (DS). As mentioned earlier all the applications must carefully analyze the relationship between the grammar of both, the destination and target languages
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