A New Approach for Extracting Named Entity in Classical Arabic

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Sajadi Seyed mohammad bagher; RASHIDI HASAN; MINAEI BEHROUZ

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Journal: SIGNAL AND DATA PROCESSING Year:2017 | Volume:14 | Issue:2 (serial 32) Page(s): 59-74

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Title

A New Approach for Extracting Named Entity in Classical Arabic

Author(s)

Sajadi Seyed mohammad bagher | RASHIDI HASAN | MINAEI BEHROUZ | Issue Writer Certificate

Keywords

Named entity recognition (NER)Q2

Ensemble learningQ1

Boosting methodQ1

Classical Arabic LanguageQ1

Abstract

In Natural Language Processing (NLP) studies, developing resources and tools makes a contribution to extension and Effectiveness of researches in each language. In recent years, Arabic Named Entity Recognition (ANER) has been considered by NLP researchers. While most of these researches are based on Modern Standard Arabic (MSA), in this paper, we focus on Classical Arabic (CA) literature. We propose a corpus called NoorCorp with 200k labeled words for research purposes which is annotated by expert human resources manually. We also collected about 18k proper names from old Hadith books as gazetteer which is called NoorGazet. Using Ensemble learning, we develop a new approach for extraction of named entities (NEs) including person, location and organization. Adaboost. M2 algorithm, as implementation of multiclass Boosting method, is applied to train the prediction model. Results show that performance of the method is better than decision tree as the base classifier. We have used tokenizing, part of speech (POS) tagging, and base phrase chunking (BPC) to overcome linguistic obstacles in Arabic. An overall F-measure value of 86. 85 is obtained. Finally, the proposed approach is applied on ANERCorp as MSA corpus and we have compared the results with NoorCorp.

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APA: Copy

Sajadi, Seyed mohammad bagher, RASHIDI, HASAN, & MINAEI, BEHROUZ. (2017). A New Approach for Extracting Named Entity in Classical Arabic. SIGNAL AND DATA PROCESSING, 14(2 (serial 32) ), 59-74. SID. https://sid.ir/paper/160751/en

Vancouver: Copy

Sajadi Seyed mohammad bagher, RASHIDI HASAN, MINAEI BEHROUZ. A New Approach for Extracting Named Entity in Classical Arabic. SIGNAL AND DATA PROCESSING[Internet]. 2017;14(2 (serial 32) ):59-74. Available from: https://sid.ir/paper/160751/en

IEEE: Copy

Seyed mohammad bagher Sajadi, HASAN RASHIDI, and BEHROUZ MINAEI, “A New Approach for Extracting Named Entity in Classical Arabic,” SIGNAL AND DATA PROCESSING, vol. 14, no. 2 (serial 32) , pp. 59–74, 2017, [Online]. Available: https://sid.ir/paper/160751/en

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