WLO
E563495
WLO is the National Rail station code used to identify London Waterloo Underground station in the UK rail network.
All labels observed (1)
| Label | Occurrences |
|---|---|
| WLO canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T6027215 — 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: WLO Context triple: [Waterloo Underground station, hasStationCode, WLO]
-
A.
WNLO
WNLO is a major Chinese research institute specializing in optoelectronics and photonics, based in Wuhan.
-
B.
WOB
WOB is the vehicle registration code used on license plates for cars registered in Wolfsburg, Germany.
-
C.
WLA
WLA is an acronym commonly used for the Women's Land Army, a civilian organization of women who worked in agriculture to support food production during wartime, particularly in the United Kingdom.
-
D.
WU
WU is a leading European university in Vienna specializing in economics, business, and social sciences.
-
E.
WU
WU is the stock ticker symbol for Western Union, a global financial services company best known for its money transfer and payment services.
- 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: WLO Target entity description: WLO is the National Rail station code used to identify London Waterloo Underground station in the UK rail network.
-
A.
WNLO
WNLO is a major Chinese research institute specializing in optoelectronics and photonics, based in Wuhan.
-
B.
WOB
WOB is the vehicle registration code used on license plates for cars registered in Wolfsburg, Germany.
-
C.
WLA
WLA is an acronym commonly used for the Women's Land Army, a civilian organization of women who worked in agriculture to support food production during wartime, particularly in the United Kingdom.
-
D.
WU
WU is a leading European university in Vienna specializing in economics, business, and social sciences.
-
E.
WU
WU is the stock ticker symbol for Western Union, a global financial services company best known for its money transfer and payment services.
- F. None of above. chosen
Statements (26)
| Predicate | Object |
|---|---|
| instanceOf |
National Rail station code
ⓘ
railway station identifier ⓘ |
| appliesTo | rail passengers ⓘ |
| associatedWith | Waterloo station ⓘ |
| codeType | three-letter station code ⓘ |
| country | United Kingdom ⓘ |
| fareZone | London fare zone 1 ⓘ |
| language | English ⓘ |
| locationBorough |
London Borough of Lambeth
ⓘ
linked to:
Lambeth
|
| locationCity |
London
ⓘ
linked to:
London, England
|
| networkRole | identifies an Underground station within the National Rail system ⓘ |
| railNetwork | National Rail ⓘ |
| railRegion |
London and South East
ⓘ
linked to:
South East England
|
| relatedLine |
Bakerloo line
ⓘ
Jubilee line ⓘ Northern line ⓘ Waterloo & City line ⓘ |
| relatedMode | London Underground ⓘ |
| serves |
London Waterloo Underground station
ⓘ
linked to:
London Waterloo railway station
|
| servesInterchangeWith | National Rail services at London Waterloo ⓘ |
| stationName |
London Waterloo Underground station
ⓘ
linked to:
London Waterloo railway station
|
| system | UK rail station coding system ⓘ |
| transportAuthority | Transport for London ⓘ |
| usedFor |
journey planning
ⓘ
railway timetables ⓘ ticketing ⓘ |
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: WLO Description of subject: WLO is the National Rail station code used to identify London Waterloo Underground station in the UK rail network.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.