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Abstract
Named Entity Recognition (NER) is an important task that is used as a pre-processing step in various natural language processing (NLP) applications. It is useful as it mostly increases the performance of NLP applications. A large number of researchers are focusing this problem using various techniques such as rule based, machine learning based and hybrid approaches. In the recent times, deep learning algorithms are also emerging for developing NER models. It is very challenging to build NER system for Hindi language in particular because it is an ambiguous, morphologically rich and resource scarce language. In this paper, we present a state-of-the-art survey covering various approaches of NER for mainly Hindi Language.
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