The Power of Named Entity Recognition (NER) in Natural Language Processing
Named Entity Recognition, often abbreviated as NER, is a subtask of NLP that involves locating and classifying named entities in text data. These named entities can span a wide range of categories, including:
>Persons
>Organizations
>Locations
>Dates
>Percentage
>Monetary Values
How does it works ?
Named Entity Recognition (NER) works by using machine learning models to identify and classify specific named entities, such as names of people, organizations, locations, and more, within a given text, based on patterns and features learned from labeled data.
For your reference : https://www.ibm.com/topics/named-entity-recognition