Triple
T21477209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Presidente Vargas Station (Rio de Janeiro Metro) |
E529891
|
entity |
| Predicate | hasPassengerBuildingType |
P50464
|
FINISHED |
| Object | subsurface station building |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: subsurface station building | Statement: [Presidente Vargas Station (Rio de Janeiro Metro), hasPassengerBuildingType, subsurface station building]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPassengerBuildingType Context triple: [Presidente Vargas Station (Rio de Janeiro Metro), hasPassengerBuildingType, subsurface station building]
-
A.
containsBuildingType
chosen
Indicates that a location or area includes at least one building of the specified type.
-
B.
hasPassengerTerminal
Indicates that one entity possesses or is equipped with a passenger terminal used for boarding, alighting, or handling passengers.
-
C.
hasPassengerTerminalFunction
Indicates that something serves the role or performs the function of a passenger terminal, supporting the handling and movement of passengers.
-
D.
hasSeatBuilding
Indicates that a seat (or seating area) is located within or belongs to a particular building.
-
E.
hasPassengerRole
Indicates that an entity participates in a context or event specifically in the capacity or role of a passenger.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e0c459acb481909bb6ee452a0045c7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea187a3c8190b3f33bd760dc1f54 |
completed | April 23, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69e631ec1d048190b6da97da8222e413 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:20 p.m.