ISSN 2321 - 9726 (Online) New DOI : 10.32804/BBSSES

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    1 Author(s):  BRIJESH KUMAR YADAV

Vol -  5, Issue- 4 ,         Page(s) : 42 - 48  (2014 ) DOI :


The term “Named Entity” (NE) is the unsolved and open ended issue for Natural Language Processing (NLP) tasks. Recognition of NE is as crucial tasks as the classification of it. To extract them firstly we have to decide how to recognize the NEs. Named entities are often mined for marketing initiatives. Several works have been done in this area within Machine Translation (MT) perspective in major languages of the world. In the context of Indian languages a very few works have been done. Though there are many information can be retrieved from the name only like personal identification, caste, dynasty, religions, locality etc. NEs also include; geographic locations, ages, addresses, phone numbers, companies and addresses in other words proper nouns. In Hindi, a major Indo-Aryan Language of Indian subcontinent this area has been initially dealt by IIT-Bombay and IIIT-Hyderabad. The research paper tries to discuss the issue of Hindi NEs and describes the ambiguity caused by them without proper identification.

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  2. Nadeau,  David:  Semi-Supervised  Named  Entity  Recognition,  University  of Ottawa, Canada, (2007)
  3. McCallum,  “Early  results  for  Named  Entity  Recognition  with  Conditional Random Fields, feature induction and web-enhanced lexicons,” in proceedings of  7th conference on Natural Language Learning at HLT NAACL 2003,
  4. W. Li and A. McCallum, “Rapid development of Hindi named entity recognition using conditional random fields and feature induction,” ACM Transactions on Asian Language Information Processing (TALIP), Vol. 2, no. 3, pp. 290-294, 2003.

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