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Named Entity Recognition for Telugu Using Conditional Random Field
G.V.S.Raju, B.Srinivasu, S. Viswanadha Raju, Allam Balaram
Pages - 36 - 44     |    Revised - 30-11-2010     |    Published - 20-12-2010
Volume - 1   Issue - 3    |    Publication Date - December 2010  Table of Contents
Named entity , Conditional Random field,, NER,, Telugu
Named Entity (NE) recognition is a task in which proper nouns and numerical information are extracted from documents and are classified into predefined categories such as Person names, Organization names , Location names, miscellaneous(Date and others). It is a key technology of Information Extraction, Question Answering system, Machine Translations, Information Retrial etc. This paper reports about the development of a NER system for Telugu using Conditional Random field (CRF). Though this state of the art machine learning technique has been widely applied to NER in several well-studied languages, the use of this technique to Telugu languages is very new. The system makes use of the different contextual information of the words along with the variety of features that are helpful in predicting the four different named entities (NE) classes, such as Person name, Location name, Organization name, miscellaneous (Date and others). Keywords: Named entity, Conditional Random field, NE, CRF, NER, named entity recognition
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Professor G.V.S.Raju
IIET - India
Associate Professor B.Srinivasu
IIET - India
S. Viswanadha Raju
- India
Assistant Professor Allam Balaram
- India