NER with BERT NER dataset to recognize the name entity from the sentences Name-entity recognition (NER) is also referred to as entity identification, entity chunking, and entity extraction. NER is the component of information extraction that aims to identify and categorize named entities within unstructured text. NER involves the identification of key information in the text and classification into a set of predefined categories. An entity is the thing that is consistently talked about or refer to in the text, such as person names, organizations, locations, time expressions, quantities, percentages and more predefined categories.

ORGANIZATION - Georgia-Pacific Corp., WHO

PERSON - Eddy Bonte, President Obama

LOCATION - Murray River, Mount Everest

DATE - June, 2008-06-29

TIME - two fifty a m, 1:30 p.m.

MONEY - 175 million Canadian Dollars, GBP 10.40

PERCENT - twenty pct, 18.75 %

FACILITY - Washington Monument, Stonehenge

GPE - South East Asia, Midlothian

Application in real life: Recomendation system