Premetro Line E2
E191066
Premetro Line E2 is a light rail feeder line in Buenos Aires that connects outlying neighborhoods to the city’s Underground network.
All labels observed (5)
| Label | Occurrences |
|---|---|
| Premetro E2 | 2 |
| Premetro Line E2 canonical | 2 |
| Premetro Line P | 2 |
| Premetro E2 (as operated asset) | 1 |
| Subte Line E operations | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T1699307 — 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: Premetro Line E2 Context triple: [Buenos Aires Underground, hasPremetro, Premetro Line E2]
-
A.
Metro Line 3
Metro Line 3 is a major Mexico City Metro route that runs north–south across the city, connecting key residential and commercial areas including the Gustavo A. Madero borough.
-
B.
Metro Line 6
Metro Line 6 is a line of the Mexico City Metro system that serves the northern part of the city, including the Gustavo A. Madero borough.
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C.
LRT Line 2
LRT Line 2 is an elevated rapid transit line in Metro Manila, Philippines, running east–west and serving major areas including Quezon City, Manila, and Pasig.
-
D.
Metro Line 54
Metro Line 54 is a rapid transit line in the Amsterdam Metro system that connects the city center with southeastern suburbs such as Bijlmermeer.
-
E.
Metro Line 53
Metro Line 53 is a rapid transit line in Amsterdam that connects the city center with the southeastern suburbs as part of the Amsterdam Metro system.
- 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: Premetro Line E2 Target entity description: Premetro Line E2 is a light rail feeder line in Buenos Aires that connects outlying neighborhoods to the city’s Underground network.
-
A.
Metro Line 3
Metro Line 3 is a major Mexico City Metro route that runs north–south across the city, connecting key residential and commercial areas including the Gustavo A. Madero borough.
-
B.
Metro Line 6
Metro Line 6 is a line of the Mexico City Metro system that serves the northern part of the city, including the Gustavo A. Madero borough.
-
C.
LRT Line 2
LRT Line 2 is an elevated rapid transit line in Metro Manila, Philippines, running east–west and serving major areas including Quezon City, Manila, and Pasig.
-
D.
Metro Line 54
Metro Line 54 is a rapid transit line in the Amsterdam Metro system that connects the city center with southeastern suburbs such as Bijlmermeer.
-
E.
Metro Line 53
Metro Line 53 is a rapid transit line in Amsterdam that connects the city center with the southeastern suburbs as part of the Amsterdam Metro system.
- F. None of above. chosen
Statements (20)
| Predicate | Object |
|---|---|
| instanceOf |
feeder line
ⓘ
light rail line ⓘ public transport route ⓘ |
| city | Buenos Aires ⓘ |
| connectsTo |
Buenos Aires Underground
ⓘ
Buenos Aires Underground Line E ⓘ |
| country | Argentina ⓘ |
| electrification | overhead line (inferred, not confirmed) ⓘ |
| hasConnectionType | interchange with metro ⓘ |
| hasTrackGauge | standard gauge (inferred, not confirmed) ⓘ |
| isPartOfSystem | Buenos Aires public transport network ⓘ |
| locatedIn |
Argentina
ⓘ
Buenos Aires ⓘ |
| networkRole | feeder to metro network ⓘ |
| operator | Buenos Aires city transport authority (inferred, not confirmed) ⓘ |
| partOf | Buenos Aires Premetro ⓘ |
| serves | outlying neighborhoods of Buenos Aires ⓘ |
| serviceType |
light rail transit
ⓘ
urban transit ⓘ |
| transportMode | light rail ⓘ |
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: Premetro Line E2 Description of subject: Premetro Line E2 is a light rail feeder line in Buenos Aires that connects outlying neighborhoods to the city’s Underground network.
Referenced by (8)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: Premetro Line E2
subject linked to:
Buenos Aires Underground public transit system
linked to: Premetro Line E2
linked to: Premetro Line E2
linked to: Premetro Line E2
linked to: Premetro Line E2