Dahua Road depot
E739556
Dahua Road depot is a maintenance and storage facility serving Shanghai Metro’s Line 7.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Dahua Road depot canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8517830 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dahua Road depot Context triple: [Line 7 (Shanghai Metro), depot, Dahua Road depot]
-
A.
Meilong Depot
Meilong Depot is a major maintenance and storage facility serving Shanghai Metro’s Line 1 in Shanghai, China.
-
B.
Wanshengwei Depot
Wanshengwei Depot is a major operations and maintenance facility serving Guangzhou Metro’s urban rail network in Guangzhou, China.
-
C.
Xilang Depot
Xilang Depot is a maintenance and storage facility serving the Guangzhou Metro system in Guangzhou, China.
-
D.
Sanyuanqiao depot
Sanyuanqiao depot is a maintenance and storage facility serving Beijing’s Capital Airport Express line.
-
E.
Daliao Depot
Daliao Depot is a maintenance and storage facility serving trains on the Kaohsiung Mass Rapid Transit system in Kaohsiung, Taiwan.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dahua Road depot Target entity description: Dahua Road depot is a maintenance and storage facility serving Shanghai Metro’s Line 7.
-
A.
Meilong Depot
Meilong Depot is a major maintenance and storage facility serving Shanghai Metro’s Line 1 in Shanghai, China.
-
B.
Wanshengwei Depot
Wanshengwei Depot is a major operations and maintenance facility serving Guangzhou Metro’s urban rail network in Guangzhou, China.
-
C.
Xilang Depot
Xilang Depot is a maintenance and storage facility serving the Guangzhou Metro system in Guangzhou, China.
-
D.
Sanyuanqiao depot
Sanyuanqiao depot is a maintenance and storage facility serving Beijing’s Capital Airport Express line.
-
E.
Daliao Depot
Daliao Depot is a maintenance and storage facility serving trains on the Kaohsiung Mass Rapid Transit system in Kaohsiung, Taiwan.
- F. None of above. chosen
Statements (22)
| Predicate | Object |
|---|---|
| instanceOf |
metro depot
ⓘ
railway maintenance facility ⓘ rolling stock depot ⓘ |
| associatedWith |
Shanghai Metro
NERFINISHED
ⓘ
Shanghai Metro Line 7 infrastructure ⓘ |
| category |
Railway depots in China
ⓘ
Shanghai Metro depots NERFINISHED ⓘ |
| country | China ⓘ |
| function |
maintenance of rolling stock
ⓘ
storage of rolling stock ⓘ |
| locatedIn |
China
ⓘ
Shanghai ⓘ |
| networkRole | operations support facility for Shanghai Metro Line 7 ⓘ |
| operator | Shanghai Metro operator ⓘ |
| owner | Shanghai Metro authorities NERFINISHED ⓘ |
| partOfSystem | Shanghai Metro NERFINISHED ⓘ |
| railwayType | urban rapid transit ⓘ |
| servedBy | Shanghai Metro Line 7 trains NERFINISHED ⓘ |
| servesLine | Shanghai Metro Line 7 NERFINISHED ⓘ |
| usedFor |
inspection of metro trains
ⓘ
repair of metro trains ⓘ stabling of metro trains ⓘ |
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: Dahua Road depot Description of subject: Dahua Road depot is a maintenance and storage facility serving Shanghai Metro’s Line 7.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.