Profsoyuznaya

E1024031

Profsoyuznaya is a Moscow Metro station serving the Kaluzhsko–Rizhskaya Line in the south of the city.

Try in SPARQL Jump to: Surface forms Statements Referenced by

All labels observed (1)

Label Occurrences
Profsoyuznaya canonical 1

Statements (46)

Predicate Object
instanceOf Moscow Metro station
underground railway station
administrativeOkrug South-Western Administrative Okrug NERFINISHED
city Moscow
country Russia
depthBelowSurface_m 7
district Akademichesky District NERFINISHED
fareCollection turnstiles
gauge 1520 mm
hasAccess subway entrances from Profsoyuznaya Street
hasAdjacentStation Akademicheskaya NERFINISHED
Novye Cheryomushki NERFINISHED
hasCode 103
hasColumns two rows of columns
hasDesignStyle Soviet modernist
hasElectrification third rail
hasFareZone single Moscow Metro zone
hasLatitude 55.677
hasLineNumber 6
hasLongitude 37.562
hasPassengerInformationSystem electronic displays
hasPlatformSurface granite
hasRussianName Профсоюзная NERFINISHED
hasSafetyFeatures CCTV surveillance
public address system
hasStationLayout single island platform with central hall
hasTicketHall underground vestibule
hasTransferTo no direct transfer
hasVestibules 2
hasWallFinish ceramic tiles
lineColor orange
lineSection Kaluzhskaya radius
locatedIn Moscow
Russia
namedAfter Profsoyuznaya Street NERFINISHED
numberOfPlatforms 1
numberOfTracks 2
openingDate 1962-10-13
operatedBy Moscow Metro NERFINISHED
ownedBy Moscow city NERFINISHED
partOfNetwork Moscow Metro NERFINISHED
platformType island platform
servesLine Kaluzhsko–Rizhskaya Line NERFINISHED
structureType deep column station
ticketingSystem Moscow Metro unified ticketing
yearOpened 1962

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: Profsoyuznaya
Description of subject: Profsoyuznaya is a Moscow Metro station serving the Kaluzhsko–Rizhskaya Line in the south of the city.

Referenced by (1)

Full triples — surface form annotated when it differs from this entity's canonical label.

Kaluzhsko–Rizhskaya Line hasStation Profsoyuznaya