King Street stop
E112640
King Street stop is a streetcar stop on Toronto’s Spadina streetcar line, serving the busy King Street corridor in the downtown core.
All labels observed (1)
| Label | Occurrences |
|---|---|
| King Street stop canonical | 1 |
Statements (20)
| Predicate | Object |
|---|---|
| instanceOf |
public transit stop
ⓘ
streetcar stop ⓘ |
| city | Toronto ⓘ |
| country | Canada ⓘ |
| locatedIn |
Canada
ⓘ
Ontario ⓘ Toronto ⓘ Downtown Toronto ⓘ
surface form:
downtown Toronto
|
| locatedNear | Spadina Avenue ⓘ |
| locatedOn | King Street ⓘ |
| modeOfTransport | streetcar ⓘ |
| onLine | Spadina streetcar line ⓘ |
| operator | Toronto Transit Commission ⓘ |
| partOfNetwork |
Toronto public transit network
ⓘ
Toronto streetcar system ⓘ |
| province | Ontario ⓘ |
| servedBy | Spadina streetcar line ⓘ |
| serves | King Street corridor ⓘ |
| servesArea | downtown core of Toronto ⓘ |
| shortName | King ⓘ |
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: King Street stop Description of subject: King Street stop is a streetcar stop on Toronto’s Spadina streetcar line, serving the busy King Street corridor in the downtown core.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.