Named Entity Recognition is one of the very useful information extraction technique to identify and classify named entities in text. These entities are pre-defined categories such a person’s names, organizations, locations, time representations, financial elements, etc.
Apart from these generic entities, there could be other specific terms that could be defined given a particular problem. These terms represent elements which have a unique context compared to the rest of the text. For example, it could be anything like operating systems, programming languages, football league team names etc. The machine learning models could be trained to categorize such custom entities which are usually denoted by proper names and therefore are mostly noun phrases in text documents.