L10 Sud
E883866
L10 Sud is a line of the Barcelona Metro network serving the southern metropolitan area with automated, driverless trains.
All labels observed (1)
| Label | Occurrences |
|---|---|
| L10 Sud canonical | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T10742603 — 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: L10 Sud Context triple: [Collblanc, metroLine, L10 Sud]
-
A.
Skudai Highway
Skudai Highway is a major roadway in Johor, Malaysia, that serves as a key route connecting the town of Skudai with other parts of the region.
-
B.
LP-3 road
LP-3 road is a regional roadway that connects to the city of El Paso, serving as part of its surrounding transport network.
-
C.
Fujin Road
Fujin Road is a metro station in Shanghai, China, serving as the northern terminus of Line 1 of the Shanghai Metro system.
-
D.
MA-10 road
The MA-10 road is a scenic mountain route that winds along Mallorca’s Serra de Tramuntana, renowned for its dramatic coastal views and access to picturesque villages.
-
E.
Julu Road
Julu Road is a historic, tree-lined street in Shanghai known for its blend of old lane houses, trendy cafes, and boutiques in the former French Concession area.
- 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: L10 Sud Target entity description: L10 Sud is a line of the Barcelona Metro network serving the southern metropolitan area with automated, driverless trains.
-
A.
Skudai Highway
Skudai Highway is a major roadway in Johor, Malaysia, that serves as a key route connecting the town of Skudai with other parts of the region.
-
B.
LP-3 road
LP-3 road is a regional roadway that connects to the city of El Paso, serving as part of its surrounding transport network.
-
C.
Fujin Road
Fujin Road is a metro station in Shanghai, China, serving as the northern terminus of Line 1 of the Shanghai Metro system.
-
D.
MA-10 road
The MA-10 road is a scenic mountain route that winds along Mallorca’s Serra de Tramuntana, renowned for its dramatic coastal views and access to picturesque villages.
-
E.
Julu Road
Julu Road is a historic, tree-lined street in Shanghai known for its blend of old lane houses, trendy cafes, and boutiques in the former French Concession area.
- F. None of above. chosen
Statements (30)
| Predicate | Object |
|---|---|
| instanceOf |
Barcelona Metro line
ⓘ
rapid transit line ⓘ |
| country | Spain ⓘ |
| fareSystem | Autoritat del Transport Metropolità integrated fare system ⓘ |
| hasAccessibility | fully accessible stations ⓘ |
| hasColor | light blue ⓘ |
| hasElectrification | third rail ⓘ |
| hasLocale |
Barcelona metropolitan area
ⓘ
linked to:
Metropolitan Area of Barcelona
|
| hasOperationMode | driverless ⓘ |
| hasOperator | Transports Metropolitans de Barcelona ⓘ |
| hasOwner |
Generalitat de Catalunya
ⓘ
linked to:
Government of Catalonia
|
| hasRollingStockType | rubber-tyred metro trains ⓘ |
| hasSafetySystem | platform screen doors on many stations ⓘ |
| hasServicePattern | urban metro service ⓘ |
| hasSignalling | CBTC ⓘ |
| hasTechnology | automatic train operation ⓘ |
| hasTrackGauge | standard gauge ⓘ |
| hasTrainOperation | fully automated ⓘ |
| hasType | underground metro line ⓘ |
| isPartOfProject |
L9/L10 project of Barcelona Metro
ⓘ
linked to:
Barcelona Metro Line L9 Sud
|
| locatedIn |
Barcelona
ⓘ
Catalonia ⓘ metropolitan area of Barcelona ⓘ |
| partOf | Barcelona Metro ⓘ |
| serves | southern metropolitan area of Barcelona ⓘ |
| sharesInfrastructureWith |
L9 Nord
ⓘ
L9 Sud ⓘ |
| system | Barcelona Metro ⓘ |
| uses |
automated trains
ⓘ
driverless trains ⓘ |
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: L10 Sud Description of subject: L10 Sud is a line of the Barcelona Metro network serving the southern metropolitan area with automated, driverless trains.
Referenced by (1)
Full triples — surface form annotated when it differs from this entity's canonical label.