Meilong Depot
E710384
Meilong Depot is a major maintenance and storage facility serving Shanghai Metro’s Line 1 in Shanghai, China.
All labels observed (2)
| Label | Occurrences |
|---|---|
| Fujin Road Depot | 1 |
| Meilong Depot canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T8077550 — 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: Meilong Depot Context triple: [Shanghai Metro Line 1, depot, Meilong Depot]
-
A.
Wanshengwei Depot
Wanshengwei Depot is a major operations and maintenance facility serving Guangzhou Metro’s urban rail network in Guangzhou, China.
-
B.
Daliao Depot
Daliao Depot is a maintenance and storage facility serving trains on the Kaohsiung Mass Rapid Transit system in Kaohsiung, Taiwan.
-
C.
Tuqiao Depot
Tuqiao Depot is a maintenance and storage facility serving trains on Beijing’s Batong Line of the subway system.
-
D.
Sanyuanqiao depot
Sanyuanqiao depot is a maintenance and storage facility serving Beijing’s Capital Airport Express line.
-
E.
Xilang Depot
Xilang Depot is a maintenance and storage facility serving the Guangzhou Metro system in Guangzhou, China.
- 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: Meilong Depot Target entity description: Meilong Depot is a major maintenance and storage facility serving Shanghai Metro’s Line 1 in Shanghai, China.
-
A.
Wanshengwei Depot
Wanshengwei Depot is a major operations and maintenance facility serving Guangzhou Metro’s urban rail network in Guangzhou, China.
-
B.
Daliao Depot
Daliao Depot is a maintenance and storage facility serving trains on the Kaohsiung Mass Rapid Transit system in Kaohsiung, Taiwan.
-
C.
Tuqiao Depot
Tuqiao Depot is a maintenance and storage facility serving trains on Beijing’s Batong Line of the subway system.
-
D.
Sanyuanqiao depot
Sanyuanqiao depot is a maintenance and storage facility serving Beijing’s Capital Airport Express line.
-
E.
Xilang Depot
Xilang Depot is a maintenance and storage facility serving the Guangzhou Metro system in Guangzhou, China.
- F. None of above. chosen
Statements (26)
| Predicate | Object |
|---|---|
| instanceOf |
metro depot
ⓘ
railway depot ⓘ transport infrastructure ⓘ |
| associatedWithMode | rapid transit ⓘ |
| associatedWithOperator | Shanghai Metro operator ⓘ |
| continent | Asia ⓘ |
| countryISOCode | CN ⓘ |
| electrificationSystemServed | third rail electrification ⓘ |
| hasFunction |
maintenance facility
ⓘ
rolling stock storage ⓘ |
| infrastructureType | rail operations base ⓘ |
| locatedInCity | Shanghai ⓘ |
| locatedInCountry | China ⓘ |
| locatedInMunicipality |
Shanghai Municipality
ⓘ
linked to:
Shanghai
|
| locatedInRegion |
East China
ⓘ
linked to:
eastern China
|
| networkRole | major depot for Line 1 ⓘ |
| partOfSystem | Shanghai Metro ⓘ |
| publicTransportSystem |
Shanghai Metro system
ⓘ
linked to:
Shanghai Metro
|
| railSystemType | metro ⓘ |
| servesCity | Shanghai ⓘ |
| servesLine | Shanghai Metro Line 1 ⓘ |
| servesNetwork |
Shanghai urban rail transit network
ⓘ
linked to:
Shanghai urban public transport network
|
| trackGauge | standard gauge ⓘ |
| 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: Meilong Depot Description of subject: Meilong Depot is a major maintenance and storage facility serving Shanghai Metro’s Line 1 in Shanghai, China.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: Meilong Depot