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A Hybrid Approach for NER System for Scarce Resourced Language-URDU: Integrating n-gram with Rules and Gazetteers Keywords: Entity Recognition, Named Entities, N-Gram Model, Gazetteer Lists Mehran University Research Journal of Engineering & Technology Volume 34 , Issue 4 Saeeda Naz,Arif Iqbal Umar,Imran Razzak Abstract We present a hybrid NER (Name Entity Recognition) system for Urdu script by integration of n-gram model (unigram and bigram), rules and gazetteers. We used prefix and suffix characters for rule construction instead of first name and last name lists or potential terms on the output list that is produced by n-gram model. Evaluation of the system is performed on two corpora, the IJCNLP NE (Named Entity) corpus and CRL NE corpus in Urdu text. The system achieved 92.65 and 87.6% using hybrid unigram and 92.47 and 86.83% using hybrid bigram on IJCNLP NE corpus and CRL NE corpus, respectively

Article Information

A Hybrid Approach for NER System for Scarce Resourced Language-URDU: Integrating n-gram with Rules and Gazetteers

Keywords: Entity Recognition, Named Entities, N-Gram Model, Gazetteer Lists

Mehran University Research Journal of Engineering & Technology

Volume 34 , Issue 4

Saeeda Naz,Arif Iqbal Umar,Imran Razzak

Abstract

We present a hybrid NER (Name Entity Recognition) system for Urdu script by integration of n-gram model (unigram and bigram), rules and gazetteers. We used prefix and suffix characters for rule construction instead of first name and last name lists or potential terms on the output list that is produced by n-gram model. Evaluation of the system is performed on two corpora, the IJCNLP NE (Named Entity) corpus and CRL NE corpus in Urdu text. The system achieved 92.65 and 87.6% using hybrid unigram and 92.47 and 86.83% using hybrid bigram on IJCNLP NE corpus and CRL NE corpus, respectively