Venkateswarlu Poka

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This paper reports about the development of a Named Entity Recognition (NER) system for South and South East Asian languages, particularly for Bengali, Hindi, Telugu, Oriya and Urdu as part of the IJCNLP-08 NER Shared Task. We have used the statistical Conditional Random Fields (CRFs). The system makes use of the different contextual information of the(More)
Named Entity Recognition (NER) seeks to locate and classify atomic elements in text into predefined categories such as names of person, organization, location, Quantities, Percentage etc. Named entities tell us the roles of each meaning bearing word in a sentence and hence identification of these entities certainly helps us to extract the essence of the(More)
  • Arindam Dey, Bipul Syam Prukayastha, +19 authors Sudha Morwal
  • 2013
Named Entity Recognition (NER) is a task to discover the Named Entities (NEs) in a document and then categorize these NEs into diverse Named Entity classes such as Name of Person, Location, River, Organization etc. Area of concentration is the performance of NER in the Indian languages (IL). Nepali is the target language. In this paper different technique(More)
The goal of this workshop is to ascertain the state of the art in Named Entity Recognition (NER) specifically for South and South East Asian (SSEA) languages. This workshop continues the work started in the NLPAI Machine Learning Contest 2007 which was focused on NER for South Asian languages. NER was selected this time for the contest as well as for this(More)
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