In Natural Language Processing research, Named entity recognition acts as an important tool. To improve the quality of search results, while searching through the internet , the automatic Named entity recognition(NER) and classification in the text plays very important role. Many natural language processing applications like question answering, document clustering, document summarization uses the output of Named Entity Recognition. Even today, the highly accurate Named Entity Recognition (NER) is a challenge, In this paper, a novel approach using unsupervised learning is proposed to automatically create gazette for Named entity recognition and Named entity extraction. The main purpose of approach is to automate the named entity recognition task, as manually recognizing named entities is cumbersome. Manually labeling so huge number of entities is effort intensive and can lead to wrong classification of entities.

Named Entity Recognition, Named Entity Extraction, Natural Language Processing, Machine Learning, Information Retrieval

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