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Media preprint DOI: https://doi.org/10.1101/2020.04.09.20058958; this version posted July 28, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder,

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What is named entity recognition applied?

Named entity recognition is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into predefined categories such as the names of persons, locations, organizations, expressions of times, quantities, monetary values, percentages, etc.

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Organizations or individuals dealing with large amounts of text data, such as corporations, government agencies, researchers, and developers, may need to use named entity recognition to extract valuable information from text.

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The purpose of named entity recognition is to help organize, classify, and extract meaningful information from unstructured text data. It is used for various applications such as information retrieval, machine translation, question answering, and sentiment analysis.

What information must be reported on named entity recognition applied?

The reported information on named entity recognition applied includes the types of named entities found in the text, their corresponding categories, and their locations within the text.

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