Xicheng (historical)
E746744
Xicheng (historical) was the former name of the city now known as Ankang in Shaanxi Province, China.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Xicheng (historical) canonical | 1 |
Statements (15)
| Predicate | Object |
|---|---|
| instanceOf |
former place name
ⓘ
historical city ⓘ |
| country | China ⓘ |
| formerNameOf | Ankang NERFINISHED ⓘ |
| hasChineseName | 西城 NERFINISHED ⓘ |
| locatedIn |
Northwest China
NERFINISHED
ⓘ
Shaanxi Province NERFINISHED ⓘ |
| locatedOn | Han River basin ⓘ |
| nameType | toponym ⓘ |
| partOf | Chinese imperial administrative system ⓘ |
| presentDayLocation | Ankang NERFINISHED ⓘ |
| region | southern Shaanxi NERFINISHED ⓘ |
| replacedBy | name Ankang ⓘ |
| status | defunct name ⓘ |
| usedIn | historical records of China ⓘ |
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: Xicheng (historical) Description of subject: Xicheng (historical) was the former name of the city now known as Ankang in Shaanxi Province, China.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.