Xicun Station
E217774
Xicun Station is a metro station in Guangzhou, China, serving passengers on the Guangzhou Metro network.
All labels observed (2)
| Label | Occurrences |
|---|---|
| Jiangnanxi station | 1 |
| Xicun Station canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T1650433 — 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: Xicun Station Context triple: [Guangzhou Metro, hasStation, Xicun Station]
-
A.
Wanshengwei Station
Wanshengwei Station is a metro station in Guangzhou, China, serving as a transport hub within the Guangzhou Metro network.
-
B.
Changshou Lu Station
Changshou Lu Station is an underground metro station on the Guangzhou Metro system serving the bustling Changshou Road commercial area in Guangzhou, China.
-
C.
Tiyu Xilu Station
Tiyu Xilu Station is a major interchange and one of the busiest metro stations in Guangzhou, China, serving as a key hub in the Guangzhou Metro network.
-
D.
Guomao station
Guomao station is a major interchange hub on the Beijing Subway, serving the central business district and connecting key metro lines.
-
E.
Zhichunlu station
Zhichunlu station is a subway station in Beijing that serves as part of the city's extensive urban rail transit network.
- 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: Xicun Station Target entity description: Xicun Station is a metro station in Guangzhou, China, serving passengers on the Guangzhou Metro network.
-
A.
Wanshengwei Station
Wanshengwei Station is a metro station in Guangzhou, China, serving as a transport hub within the Guangzhou Metro network.
-
B.
Changshou Lu Station
Changshou Lu Station is an underground metro station on the Guangzhou Metro system serving the bustling Changshou Road commercial area in Guangzhou, China.
-
C.
Tiyu Xilu Station
Tiyu Xilu Station is a major interchange and one of the busiest metro stations in Guangzhou, China, serving as a key hub in the Guangzhou Metro network.
-
D.
Guomao station
Guomao station is a major interchange hub on the Beijing Subway, serving the central business district and connecting key metro lines.
-
E.
Zhichunlu station
Zhichunlu station is a subway station in Beijing that serves as part of the city's extensive urban rail transit network.
- F. None of above. chosen
Statements (25)
| Predicate | Object |
|---|---|
| instanceOf |
metro station
ⓘ
railway station ⓘ |
| city | Guangzhou ⓘ |
| country | China ⓘ |
| hasAccessibility | accessible to disabled passengers ⓘ |
| hasFacility |
customer service center
ⓘ
elevators ⓘ escalators ⓘ restrooms ⓘ security checkpoints ⓘ stairs ⓘ ticket vending machines ⓘ |
| hasFareSystem | Guangzhou Metro fare system ⓘ |
| hasOperator | Guangzhou Metro ⓘ |
| hasPlatformType | island platform ⓘ |
| hasTicketing |
automatic fare collection
ⓘ
contactless smart card ⓘ |
| hasUsage | urban public transport ⓘ |
| isPartOfNetwork | urban rail transit in Guangzhou ⓘ |
| locatedIn |
Guangzhou
ⓘ
Liwan District ⓘ |
| partOf | Guangzhou Metro ⓘ |
| serves |
Guangzhou Metro network
ⓘ
linked to:
Guangzhou Metro
|
| servesFunction | passenger transport ⓘ |
| structureType | underground ⓘ |
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: Xicun Station Description of subject: Xicun Station is a metro station in Guangzhou, China, serving passengers on the Guangzhou Metro network.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: Xicun Station