CERN
E112771
CERN is the stock ticker symbol for Cerner Corporation, a major American health information technology company known for its electronic health record systems.
All labels observed (1)
| Label | Occurrences |
|---|---|
| CERN canonical | 2 |
Statements (49)
| Predicate | Object |
|---|---|
| instanceOf |
health information technology company
ⓘ
public company ⓘ stock ticker symbol ⓘ |
| acquiredBy | Oracle Corporation ⓘ |
| acquisitionAnnounced | 2021 ⓘ |
| acquisitionCompleted | 2022 ⓘ |
| country |
United States of America
ⓘ
surface form:
United States
|
| countryOfHeadquarters |
United States of America
ⓘ
surface form:
United States
|
| focusesOn |
clinical workflows
ⓘ
digitization of medical records ⓘ health data interoperability ⓘ healthcare data analytics ⓘ |
| formerName | PGI & Associates ⓘ |
| foundedBy |
Cliff Illig
ⓘ
Neal Patterson ⓘ Paul Gorup ⓘ |
| hasClient |
healthcare organizations worldwide
ⓘ
hospitals in the United States ⓘ |
| hasCompetitor |
Allscripts
ⓘ
Epic Systems ⓘ MEDITECH ⓘ |
| hasProduct |
Cerner
ⓘ
surface form:
Cerner Millennium
HealtheIntent ⓘ PowerChart ⓘ |
| headquartersLocation | North Kansas City, Missouri ⓘ |
| inception | 1979 ⓘ |
| industry |
electronic health records
ⓘ
health information technology ⓘ healthcare IT ⓘ |
| knownFor |
EHR software
ⓘ
electronic health record systems ⓘ health information technology solutions ⓘ |
| languageOfProducts | English ⓘ |
| legalForm | corporation ⓘ |
| listedOn | NASDAQ ⓘ |
| locatedInTimeZone | Central Time Zone ⓘ |
| offersService |
clinical information systems
ⓘ
healthcare analytics ⓘ interoperability solutions ⓘ population health management ⓘ revenue cycle management ⓘ |
| parentOrganization | Oracle Corporation ⓘ |
| represents |
Cerner
ⓘ
surface form:
Cerner Corporation
|
| servesIndustry |
health systems
ⓘ
hospitals ⓘ physician practices ⓘ |
| stockExchange | NASDAQ ⓘ |
| stockTicker | CERN self-linksurface differs ⓘ |
| website | https://www.cerner.com/ ⓘ |
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: CERN Description of subject: CERN is the stock ticker symbol for Cerner Corporation, a major American health information technology company known for its electronic health record systems.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject surface form:
Cerner Corporation