A hybrid method for extracting relations between Arabic named entities | Zendy

Ines Boujelben | Zendy; Salma Jamoussi | Zendy; Abdelmajid Ben Hamadou | Zendy

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A hybrid method for extracting relations between Arabic named entities

Author(s) -

Ines Boujelben,

Salma Jamoussi,

Abdelmajid Ben Hamadou

Publication year - 2014

Publication title -

journal of king saud university - computer and information sciences

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.617

H-Index - 33

eISSN - 2213-1248

pISSN - 1319-1578

DOI - 10.1016/j.jksuci.2014.06.004

Subject(s) - automatic summarization , computer science , natural language processing , artificial intelligence , relation (database) , arabic , task (project management) , relationship extraction , question answering , modern standard arabic , natural language , information extraction , linguistics , data mining , philosophy , management , economics

Relation extraction is a very useful task for several natural language processing applications, such as automatic summarization and question answering. In this paper, we present our hybrid approach to extracting relations between Arabic named entities. Given that Arabic is a rich morphological language, we build a linguistic and learning model to predict the positions of words that express a semantic relation within a clause. The main idea is to employ linguistic modules to ameliorate the results that are obtained from a machine learning-based method.Our method achieves encouraging performance. The empirical results indicate that the hybrid approach outperformed both the rule-based system (by 12%) and the machine learning-based approaches (by 9%) in terms of the F-score, to achieve 75.2% when applied to the same standard testing dataset, ANERCorp

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