Named Entity Recognition Multilingual/19 entities

Project Unsupervised Cross-lingual Learning


Named Entity Recognition (NER) classifies tokens in text into predefined categories (tags), such as person names, quantity expressions, percentage expressions, names of locations, organizations, as well as expression of time, currency and others. We can recognize up to 19 entities. Navioo also features a multilingual model that is available for 104 languages. NER can be used as a knowledge extractor when you are interested in a piece of certain information in your text.


Click on an entity to see its class description
Classes: PERSON
People, including fictional.
NORP
Nationalities or religious or political groups.
ORG
Companies, agencies, institutions, etc.
LOC
Non-GPE locations, mountain ranges, bodies of water.
GPE
Countries, cities, states.
DATE
Absolute or relative dates or periods.
MONEY
Monetary values, including unit.
FAC
Buildings, airports, highways, bridges, etc.
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.
TIME
Times smaller than a day.
PERCENT
Percentage, including "%".
QUANTITY
Measurements, as of weight or distance.
ORDINAL
"first", "second", etc.
CARDINAL
Numerals that do not fall under another type.
Text ( multilang )

Results
Entity