Liễu Giai Street
E760047
Liễu Giai Street is a major urban thoroughfare in Hanoi, Vietnam, known for its embassies, high-end residences, and proximity to key administrative and commercial areas.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Liễu Giai Street canonical | 1 |
Statements (19)
| Predicate | Object |
|---|---|
| instanceOf | street ⓘ |
| city | Hanoi ⓘ |
| country |
Viet Nam
ⓘ
surface form:
Vietnam
|
| hasCharacteristic |
high real estate value
ⓘ
mixed residential and institutional land use ⓘ |
| hasFunction | major traffic artery ⓘ |
| hasLanguageOfToponym | Vietnamese ⓘ |
| knownFor |
embassies
ⓘ
high-end residences ⓘ proximity to administrative areas ⓘ proximity to commercial areas ⓘ |
| locatedIn |
Ba Đình District
NERFINISHED
ⓘ
Hanoi ⓘ |
| partOf | Hanoi road network ⓘ |
| transportRole | connector between key districts in Hanoi ⓘ |
| urbanContext | central Hanoi NERFINISHED ⓘ |
| usedFor |
access to diplomatic missions
ⓘ
access to residential areas ⓘ commuting ⓘ |
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: Liễu Giai Street Description of subject: Liễu Giai Street is a major urban thoroughfare in Hanoi, Vietnam, known for its embassies, high-end residences, and proximity to key administrative and commercial areas.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.