Gruta de Lourdes station
E296092
Gruta de Lourdes station is a stop on Santiago, Chile’s Metro system, serving passengers along Line 5.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Gruta de Lourdes station canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T2759755 — 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: Gruta de Lourdes station Context triple: [Line 5 (Santiago Metro), hasStation, Gruta de Lourdes station]
-
A.
Lyon-Jean Macé station
Lyon-Jean Macé station is a railway and multimodal transport hub in Lyon, France, serving regional and local commuter traffic and providing an additional central access point to the city’s rail network.
-
B.
St. Denis station
St. Denis station is a MARC commuter rail stop in Maryland serving passengers on the Camden Line between Washington, D.C., and Baltimore.
-
C.
Legarda station
Legarda station is an elevated rapid transit stop on Manila’s LRT Line 2 serving the Sampaloc area and nearby universities.
-
D.
Pape station
Pape station is a subway station in Toronto, Ontario, serving the city's Bloor–Danforth line in the Greektown area.
-
E.
Salaryevo station
Salaryevo station is a Moscow Metro station on the Sokolnicheskaya Line serving the southwestern outskirts of the city.
- 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: Gruta de Lourdes station Target entity description: Gruta de Lourdes station is a stop on Santiago, Chile’s Metro system, serving passengers along Line 5.
-
A.
Lyon-Jean Macé station
Lyon-Jean Macé station is a railway and multimodal transport hub in Lyon, France, serving regional and local commuter traffic and providing an additional central access point to the city’s rail network.
-
B.
St. Denis station
St. Denis station is a MARC commuter rail stop in Maryland serving passengers on the Camden Line between Washington, D.C., and Baltimore.
-
C.
Legarda station
Legarda station is an elevated rapid transit stop on Manila’s LRT Line 2 serving the Sampaloc area and nearby universities.
-
D.
Pape station
Pape station is a subway station in Toronto, Ontario, serving the city's Bloor–Danforth line in the Greektown area.
-
E.
Salaryevo station
Salaryevo station is a Moscow Metro station on the Sokolnicheskaya Line serving the southwestern outskirts of the city.
- F. None of above. chosen
Statements (25)
| Predicate | Object |
|---|---|
| instanceOf |
metro station
ⓘ
railway station ⓘ |
| continent | South America ⓘ |
| country | Chile ⓘ |
| fareMedium | Bip! card ⓘ |
| fareSystem | Santiago Metro fare system ⓘ |
| hasAccessibility | public transit access ⓘ |
| hasElectrification | electric traction ⓘ |
| hasFunction | passenger transport ⓘ |
| hasLanguage | Spanish ⓘ |
| hasPlatformType | island platform ⓘ |
| isPartOfSystem | public transport in Santiago ⓘ |
| line | Line 5 ⓘ |
| locatedIn |
Chile
ⓘ
Santiago ⓘ |
| operator | Metro S.A. ⓘ |
| owner | Metro S.A. ⓘ |
| partOf | Santiago Metro ⓘ |
| railGauge | standard gauge ⓘ |
| servedBy | Line 5 ⓘ |
| servesCity | Santiago ⓘ |
| servesMetropolitanArea |
Santiago Metropolitan Region
ⓘ
surface form:
Greater Santiago
|
| serviceType |
rapid transit
ⓘ
urban rail ⓘ |
| transportNetwork | Santiago Metro ⓘ |
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: Gruta de Lourdes station Description of subject: Gruta de Lourdes station is a stop on Santiago, Chile’s Metro system, serving passengers along Line 5.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject surface form:
Line 5 (Santiago Metro)