Named-entity recognition (NER) is a field in NLP that tags mentions of named entities in unstructured text. Named entities are the names of people, places, organizations, and more. For example, consider the following sentence:
In this sentence, there are three named entities. Tim Cook is the name of a person, New York is the name of a city (that is, location), and Apple is the name of an organization. Hence, we need an NER model that can detect these entities. Note that Apple is an ambiguous noun, as it can be the name of a company or a fruit. The NER algorithm should understand the context in which the term is used and identify it accordingly.
AWS Comprehend offers a good NER tool that can be used to identify entities. This tool can be used in real time through their dashboard...
