Craig Shelburne
E496910
Craig Shelburne is an American entrepreneur best known as one of the co-founders of the wireless home audio company Sonos.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Craig Shelburne canonical | 1 |
Statements (18)
| Predicate | Object |
|---|---|
| instanceOf |
businessperson
ⓘ
entrepreneur ⓘ |
| activeIn | 21st century ⓘ |
| coFounderOf | Sonos NERFINISHED ⓘ |
| fieldOfWork |
consumer electronics
ⓘ
home audio systems ⓘ wireless audio technology ⓘ |
| gender | male ⓘ |
| hasEmployer | Sonos NERFINISHED ⓘ |
| hasRole | executive at Sonos ⓘ |
| industry |
audio equipment industry
ⓘ
technology industry ⓘ |
| knownFor | co-founding Sonos ⓘ |
| languageOfWorkOrName | English ⓘ |
| nationality | United States of America ⓘ |
| notableWork | development of Sonos business operations ⓘ |
| occupation | entrepreneur ⓘ |
| residence | United States of America ⓘ |
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: Craig Shelburne Description of subject: Craig Shelburne is an American entrepreneur best known as one of the co-founders of the wireless home audio company Sonos.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.