Mar de Cristal station
E607643
Mar de Cristal station is a Madrid Metro station in the Hortaleza district that serves as a key interchange between multiple metro lines and nearby residential and commercial areas.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Mar de Cristal station canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T6556231 — 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: Mar de Cristal station Context triple: [Line 8 (Madrid Metro), hasInterchange, Mar de Cristal station]
-
A.
La Raza station
La Raza station is a major Mexico City Metro interchange known for connecting multiple lines and serving as an important transit hub in the city’s northern area.
-
B.
Tasqueña station
Tasqueña station is a major southern transit hub in Mexico City that serves as the terminus for the Tren Ligero light rail and connects with the city’s metro and bus networks.
-
C.
Luz Station
Luz Station is a historic railway station and major transportation hub in São Paulo, Brazil, known for its distinctive architecture and cultural significance.
-
D.
La Cisterna station
La Cisterna station is a major interchange and southern endpoint of Santiago’s metro network, connecting Line 4A with other lines and local transport services.
-
E.
La Granja station
La Granja station is a stop on Madrid Metro’s Line 4A serving the La Granja area in the city’s rapid 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: Mar de Cristal station Target entity description: Mar de Cristal station is a Madrid Metro station in the Hortaleza district that serves as a key interchange between multiple metro lines and nearby residential and commercial areas.
-
A.
La Raza station
La Raza station is a major Mexico City Metro interchange known for connecting multiple lines and serving as an important transit hub in the city’s northern area.
-
B.
Tasqueña station
Tasqueña station is a major southern transit hub in Mexico City that serves as the terminus for the Tren Ligero light rail and connects with the city’s metro and bus networks.
-
C.
Luz Station
Luz Station is a historic railway station and major transportation hub in São Paulo, Brazil, known for its distinctive architecture and cultural significance.
-
D.
La Cisterna station
La Cisterna station is a major interchange and southern endpoint of Santiago’s metro network, connecting Line 4A with other lines and local transport services.
-
E.
La Granja station
La Granja station is a stop on Madrid Metro’s Line 4A serving the La Granja area in the city’s rapid transit network.
- F. None of above. chosen
Statements (47)
| Predicate | Object |
|---|---|
| instanceOf |
Madrid Metro station
ⓘ
underground railway station ⓘ |
| accessible | yes ⓘ |
| connectsTo | Madrid-Barajas Airport via Line 8 ⓘ |
| country | Spain ⓘ |
| fareZone | A ⓘ |
| hasAutomaticFareGates | yes ⓘ |
| hasBicycleFacilities | limited or none ⓘ |
| hasCode | not publicly used (Madrid Metro generally does not use public station codes) ⓘ |
| hasConnection | urban bus services ⓘ |
| hasCustomerServicePoint | yes ⓘ |
| hasEmergencyExits | yes ⓘ |
| hasEscalators | yes ⓘ |
| hasFireSafetyEquipment | yes ⓘ |
| hasLift | yes ⓘ |
| hasLightingType | fluorescent and LED lighting ⓘ |
| hasPlatformScreenDoors | no ⓘ |
| hasPlatformType | island platform ⓘ |
| hasPublicAddressSystem | yes ⓘ |
| hasSeatingOnPlatform | yes ⓘ |
| hasSecurityCameras | yes ⓘ |
| hasSignageLanguage |
English
ⓘ
Spanish ⓘ |
| hasStructureType | underground ⓘ |
| hasTicketHall | yes ⓘ |
| hasTicketMachines | yes ⓘ |
| hasVentilationSystem | yes ⓘ |
| hasWiFi | yes (Madrid Metro WiFi service in many stations) ⓘ |
| isInterchangeBetween |
Line 4 of the Madrid Metro
NERFINISHED
ⓘ
Line 8 of the Madrid Metro NERFINISHED ⓘ |
| line4OpeningDate | 1998 ⓘ |
| line8OpeningDate | 1998 ⓘ |
| locatedIn |
Community of Madrid
ⓘ
Hortaleza district NERFINISHED ⓘ Madrid ⓘ |
| locatedInCountry | Spain NERFINISHED ⓘ |
| namedAfter | Mar de Cristal neighbourhood ⓘ |
| openingDate | 1998 ⓘ |
| operatedBy | Metro de Madrid NERFINISHED ⓘ |
| ownedBy | Consorcio Regional de Transportes de Madrid NERFINISHED ⓘ |
| partOf | Madrid Metro NERFINISHED ⓘ |
| safetySystem | CCTV monitoring ⓘ |
| serves |
Line 4 of the Madrid Metro
NERFINISHED
ⓘ
Line 8 of the Madrid Metro NERFINISHED ⓘ |
| servesArea |
commercial areas of Hortaleza
ⓘ
residential areas of Hortaleza ⓘ |
| ticketingSystem | contactless smartcard (Tarjeta Transporte Público) NERFINISHED ⓘ |
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: Mar de Cristal station Description of subject: Mar de Cristal station is a Madrid Metro station in the Hortaleza district that serves as a key interchange between multiple metro lines and nearby residential and commercial areas.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.