A Survey on Various Approach used in Named Entity Recognition for Indian Languages

Named Entity Recognition (NER) is an application of Natural Language Processing (NLP). NER is a activity of Information Extraction. NER is a task used for automated text processing for various industries, key concept for academics, artificial intelligence, robotics, Bioinformatics and many more. NER is always essential when dealing with chief NLP activity such as machine translation, question-answering, document summarization etc. Most NER work has been done for other European languages. Among Indian constitutional languages, NER work has been done for few languages. Not enough work is possible due to some challenges such as lack of resources, ambiguity in language, morphologically rich and many more. In this paper, we found many challenges available in NER for Indian languages and compared by measuring standard evaluation metrics values of accuracy, precision, recall and F-measure.