Spacy Part 2

Learn more details about Spacy in this lesson.

Named Entity Recognition

If we check Wikipedia we get to know the following definition of Named Entity Recognition (NER).

Named Entity Recognition (NER), also known as entity identification, entity chunking, and entity extraction is a subtask of information extraction that seeks to locate and classify a named entity mentioned in unstructured text into pre-defined categories. These categories could include things like person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc.

Spacy provides the following named entities.

Type Description
PERSON People, including fictional.
NORP Nationalities or religious and political groups
FAC Buildings, airports, highways, bridges, etc.
ORG Companies, agencies, institutions, etc.
GPE Countries, cities, states.
LOC Non-GPE locations, mountain ranges, and bodies of water
PRODUCT Objects, vehicles, foods, etc. (Not services)
EVENT Named hurricanes, battles, wars, sports events, etc.
WORK_OF_ART Titles of books, songs, etc.
LAW Named documents made into laws.
LANGUAGE Any named language.
DATE Absolute or relative dates or periods.
TIME Times smaller than a day.
PERCENT Percentage, including ”%“.
MONEY Monetary values, including unit.
QUANTITY Measurements, as of weight or distance.
ORDINAL “first”, “second”, etc.
CARDINAL Numerals that do not fall under another type.

Coding exercise

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