The NERExtractor function takes input documents and extracts specified entities, using one or more CRF models (output by the function NERTrainer) and, if appropriate, rules (regular expressions) or a dictionary.
The function uses models to extract the names of persons, locations, and organizations; rules to extract entities that conform to rules (such as phone numbers, times, and dates); and a dictionary to extract known entities.
NERExtractor uses files that are preinstalled on the ML Engine. For details, see Preinstalled Files That Functions Use.