Urdu Named Entity Recognition and Classification System Using Conditional Random Field
نویسندگان
چکیده
URDU NAMED ENTITY RECOGNITION AND CLASSIFICATION SYSTEM USING CONDITIONAL RANDOM FIELD Muhammad Kamran Malik, Syed Mansoor Sarwar Punjab University College of Information Technology (PUCIT), University of the Punjab, Lahore Pakistan Corresponding Author: [email protected] ABSTRACT: Named Entity Recognition (NER) system for the Urdu language based on Conditional Random Field (CRF) is described. Only three Named Entities, i.e., Person, Organization and Location names, are considered to obtain results for precision, recall, and f-measure. Our system yields 63.72%, 62.30%, and 63.00% as values for precision, recall, and fmeasure, respectively. These are the best-reported results for the Urdu language using any statistical model. We also identify some language independent features to show that a NER system can be developed for languages that have limited linguistic resources.
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