Xilang station
E854691
Xilang station is a metro station in Guangzhou, China, serving as a terminus on the city's Line 1.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Xilang station canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T9912305 — 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: Xilang station Context triple: [Line 1 (Guangzhou Metro), hasTerminus, Xilang station]
-
A.
Gangxia station
Gangxia station is a metro station in Shenzhen, China, serving as part of the city’s rapid transit network.
-
B.
Ximen Station
Ximen Station is a major Taipei Metro interchange station in the Ximending shopping and entertainment district of Taipei, Taiwan.
-
C.
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.
-
D.
Haizhu Square Station
Haizhu Square Station is a major underground metro station in central Guangzhou, China, serving as a key transit point near the Pearl River and the historic Haizhu Square area.
-
E.
Xicun Station
Xicun Station is a metro station in Guangzhou, China, serving passengers on the Guangzhou Metro 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: Xilang station Target entity description: Xilang station is a metro station in Guangzhou, China, serving as a terminus on the city's Line 1.
-
A.
Gangxia station
Gangxia station is a metro station in Shenzhen, China, serving as part of the city’s rapid transit network.
-
B.
Ximen Station
Ximen Station is a major Taipei Metro interchange station in the Ximending shopping and entertainment district of Taipei, Taiwan.
-
C.
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.
-
D.
Haizhu Square Station
Haizhu Square Station is a major underground metro station in central Guangzhou, China, serving as a key transit point near the Pearl River and the historic Haizhu Square area.
-
E.
Xicun Station
Xicun Station is a metro station in Guangzhou, China, serving passengers on the Guangzhou Metro network.
- F. None of above. chosen
Statements (21)
| Predicate | Object |
|---|---|
| instanceOf |
Guangzhou Metro station
ⓘ
metro station ⓘ |
| country | China ⓘ |
| fareZone | Guangzhou Metro fare system ⓘ |
| hasLanguage |
Chinese
ⓘ
English ⓘ |
| hasStationCode | not publicly standardized (Guangzhou Metro) ⓘ |
| line |
Line 1 (Guangzhou Metro)
ⓘ
linked to:
Guangzhou Metro Line 1
|
| locatedIn |
Guangzhou
ⓘ
Liwan District ⓘ |
| locatedInTimeZone | China Standard Time ⓘ |
| numberOfPlatforms | 2 ⓘ |
| numberOfTracks | 2 ⓘ |
| operator | Guangzhou Metro ⓘ |
| ownedBy | Guangzhou Metro ⓘ |
| partOfNetwork | Guangzhou Metro ⓘ |
| platformType | island platform ⓘ |
| role | terminus of Line 1 (Guangzhou Metro) ⓘ |
| serves | Guangzhou Metro Line 1 ⓘ |
| structureType | underground station ⓘ |
| utcOffset | +08:00 ⓘ |
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: Xilang station Description of subject: Xilang station is a metro station in Guangzhou, China, serving as a terminus on the city's Line 1.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.