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International Journal of Computer Applications (0975 8887) Volume 73 No.14, July 2013 Named Entity Recognition using Statistical Model Approach Part Padmanabhan Department of Computer Science and

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Named entity recognition (NER) is using machine learning and natural language processing techniques to identify and classify named entities in text data.

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Organizations and individuals who need to extract and analyze named entities from large amounts of text data are required to use named entity recognition.

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Named entity recognition is typically filled out by providing text data to a NER model or software tool, which then processes the data and identifies named entities within it.

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The purpose of named entity recognition is to extract and categorize specific entities such as names of people, organizations, locations, dates, etc. from text data for various applications like information retrieval, question answering, sentiment analysis, etc.

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The information reported on named entity recognition typically includes the identified named entities along with their corresponding categories and positions in the text data.

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