Pre-trained Entities

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Entity Code: pre-trained

To help you get started we have 36 entity extractors you can use off-the-shelf.

Entity Catalog

Entity	Description
person	People, including fictional
location	Non-GPE (Geo-Political Entity) locations, mountain ranges, bodies of water
miscellaneous	Miscellaneous
norp	Nationalities or religious or political groups
facility	Buildings, airports, highways, bridges, etc
organization	Companies, agencies, institutions, etc.
geo-political-entities	Countries, cities, states
product	Vehicles, weapons, 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”
cardinal	Numerals that do not fall under another type
movement	Global movements
pet-name	Pet names
phone	Phone numbers
title-affix	'Mr.' or 'Shri' or 'Mahatma' or 'Chakravarti' (as in 'Chakravarti Rajagopalachari')
designation	'Chairman' (as in 'Chairman Mao') or just 'The Chair' or 'President' (as in 'President Bush') or 'Baadshaah' (as in 'Baadshaah Akbar')
abbreviation	'IBM' (or I.B.M.) or 'CRF' or 'APJ' or 'KKK' or 'VHP'
brand	'Fanta' or 'Windows' or 'Linux' or 'Thumbs Up' or 'HP Laserjet 5M'
title-object	'The Seven Year Itch' or 'American Beauty' or '1984' (as in '1984 by George Orwell') or 'One Hundred Years of Solitude'
measure	‘Five kilos', 'three days', 'seven years'
terms	'Horticulture', 'Conditional Random Fields', 'Sociolinguistics', 'The Butterfly Effect'
credit-card-number	Credit card numbers like 4111-1111-1111-1111
distance	Distance, e.g., 6 miles
duration	Time duration, e.g., 3 mins
email	Email, e.g., a@b.com
temperature	Temperature, e.g., 80F
url	URLs, e.g., www.a.com, https://hello.com
volume	Volume, e.g., 4 gallons
pnr	PNR codes

Entities by Language

Different languages support a different set of entities.

Language	Language Code	Entities
Hindi	hi	ordinal phone person duration location money cardinal organization url email temperature
Telugu	te	phone person location money cardinal organization url email
Swedish	sv	ordinal person duration location event time distance cardinal organization
Finnish	fi	location organization cardinal person
Arabic	ar	ordinal volume person duration location time cardinal organization quantity temperature
Catalan	ca	ordinal volume url duration money distance cardinal time temperature
Croatian	hr	ordinal volume duration time distance cardinal quantity temperature
Czech	cs	distance cardinal
Estonian	et	ordinal person location organization cardinal
Hungarian	hu	ordinal person duration location time cardinal organization
Irish	ga	ordinal volume duration time distance cardinal temperature
Slovak	sk	cardinal
Bulgarian	bg	ordinal person duration location time distance cardinal organization
Turkish	tr	ordinal volume person duration location time distance cardinal organization temperature
Ukrainian	uk	duration ordinal time cardinal
Hebrew	he	ordinal person duration location time cardinal organization
Indonesian	id	ordinal person location organization cardinal
Korean	ko	ordinal volume person duration location time distance cardinal organization quantity temperature
Vietnamese	vi	ordinal person duration location time cardinal organization
Bengali	bn	location organization cardinal person
Kannada	kn	cardinal
Malayalam	ml	ordinal person location organization cardinal
Afrikaans	af	location organization cardinal person
Tamil	ta	ordinal person location organization cardinal
Persian	fa	location organization cardinal person
Danish	da	ordinal phone person location money time organization cardinal miscellaneous url email
Norwegian Bokmål	nb	ordinal phone person location duration money time organization cardinal miscellaneous url email
Greek	el	ordinal person product location event geo-political-entities duration time organization cardinal
English	en	volume date money work-of-art cardinal quantity url email phone duration percent organization law language norp ordinal person product location event geo-political-entities time distance facility temperature
Chinese	zh	date money work-of-art cardinal quantity duration percent organization law language norp ordinal person product location event geo-political-entities time distance facility temperature
Dutch	nl	volume date money work-of-art cardinal quantity duration percent organization law language norp ordinal person product location event geo-political-entities time distance facility
French	fr	ordinal volume person location duration time distance organization cardinal quantity miscellaneous temperature
German	de	ordinal volume person location duration time distance organization cardinal miscellaneous
Italian	it	ordinal volume person location duration time distance organization cardinal miscellaneous temperature
Portuguese	pt	ordinal volume person location duration time distance organization cardinal quantity miscellaneous temperature
Polish	pl	ordinal person location geo-political-entities date time duration organization cardinal
Japanese	ja	title-affix date money work-of-art cardinal quantity phone duration percent organization law language pet-name norp ordinal person product location event geo-political-entities time facility movement temperature
Romanian	ro	volume date money work-of-art cardinal quantity duration percent organization law language norp ordinal person product location event geo-political-entities time distance facility temperature
Russian	ru	ordinal volume person location duration time distance organization cardinal quantity
Spanish	es	ordinal volume person location duration time distance organization cardinal quantity miscellaneous temperature
Lithuanian	lt	product person location geo-political-entities time organization
Basque	eu	location organization person
Kazakh	kk	location organization person
Marathi	mr	location organization person
Urdu	ur	location organization person

Pre-trained Entities in Entity Recognition Models

To use a pre-trained entities in your Entity Recognition models you will have to tag at least one training example with it. Additionally, you will have to set the entityType attribute of the entity to pre-trained.

note

Make sure the name of the entity you use matches one of the supported

Sample training example

{
    "projectId": "YOUR-PROJECT-ID",
    "language": "en",
    "example": {
        "intent": "set_alarm",
        "text": "set an alarm for 25 minutes .",
        "type": "train",
        "entities": [
            {
                "entity": "time",
                "value": "for 25 minutes",
                "start": 13,
                "end": 27,
                "entityType": "pre-trained"
            }
        ]
    }
}