Named Entity Recognition (NER) is the task of identifying named entities and their class. A lot of NER models are based upon Wikipedia-generated training data for 3 NER categories: persons, locations, organizations. This is a rather simple NER annotation scheme, but available for multiple languages. The Ontonotes training data provides a more fine-grained annotation scheme, like the table below. It all depends how schema’s are defined and how training data is created. Domain specific text requires custom models, like for Legal and Biomedical. You can also get inspiration from schema.org.
This article is part of the project Periodic Table of NLP Tasks. Click to read more about the making of the Periodic Table and the project to systemize NLP tasks.