HLN
E22803
HLN is an American cable news channel, originally launched as CNN Headline News, that focuses on concise news updates and true-crime programming.
All labels observed (2)
Statements (46)
| Predicate | Object |
|---|---|
| instanceOf |
American television network
ⓘ
cable news channel ⓘ television channel ⓘ |
| availableIn |
high definition
ⓘ
standard definition ⓘ |
| broadcastArea |
Canada
ⓘ
Caribbean ⓘ United States of America ⓘ
surface form:
United States
|
| countryOfOrigin |
United States of America
ⓘ
surface form:
United States
|
| currentName | HLN self-link ⓘ |
| distributionPlatform |
IPTV
ⓘ
cable television ⓘ satellite television ⓘ streaming television ⓘ |
| formerName |
CNN
ⓘ
surface form:
CNN Headline News
CNN2 ⓘ |
| genre |
news
ⓘ
true crime ⓘ |
| headquartersLocation |
Atlanta
ⓘ
surface form:
Atlanta, Georgia
|
| language | English ⓘ |
| laterShiftedTo |
personality-driven news and talk shows
ⓘ
true-crime focused schedule ⓘ |
| launchDate | 1982-01-01 ⓘ |
| networkType | pay television network ⓘ |
| notableProgrammingType |
live news updates
ⓘ
taped true-crime series ⓘ |
| originalNetworkName |
CNN
ⓘ
surface form:
CNN Headline News
CNN2 ⓘ |
| originatedAs | 24-hour rolling news channel ⓘ |
| ownedBy |
Warner Bros. Discovery
ⓘ
Warner Bros. Discovery ⓘ
surface form:
Warner Bros. Discovery Networks
|
| ownerHistory |
Warner Bros. Discovery
ⓘ
surface form:
AT&T (through WarnerMedia)
Turner Broadcasting System ⓘ Warner Bros. Discovery ⓘ |
| parentCompany | Warner Bros. Discovery ⓘ |
| partOf |
CNN
ⓘ
surface form:
CNN Worldwide
|
| pictureFormat |
1080i HDTV
ⓘ
480i SDTV ⓘ |
| programmingFocus |
concise news updates
ⓘ
crime documentaries ⓘ headline news ⓘ true-crime programming ⓘ |
| sisterChannel |
CNN
ⓘ
CNN ⓘ
surface form:
CNN International
CNN en Español ⓘ |
| targetAudience | general audience ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: HLN Description of subject: HLN is an American cable news channel, originally launched as CNN Headline News, that focuses on concise news updates and true-crime programming.
Referenced by (16)
Full triples — surface form annotated when it differs from this entity's canonical label.
this entity surface form:
CNN