Named Entity Recognition for Telugu Language
Journal Title: International Journal of Computational Engineering and Management IJCEM - Year 2017, Vol 20, Issue 1
Abstract
Named entity recognition (NER) is a subtask of information extraction that seeks to locate and classify elements in text into predefined categories such as names of persons, locations, organizations, date, measures etc; NER has many applications in Natural Language Processing (NLP). Data classification, more accurate internet search engines, automatic indexing of documents, automatic question answering, cross language information access, and machine translation system etc are applications of NER in NLP. This paper describes about the development of a two stage hybrid Named Entity Recognition system for Telugu language. We have used Maximum Entropy Model in this system. We have used variety of features and contextual information for predicting the various Named Entity (NE) classes. We have also tried to identify the nested named Entities by giving some linguistic rules.
Authors and Affiliations
M. Humera Khanam P. Udayasri
Keywords
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