Triple
T32983210
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frunzenskaya metro station |
E843861
|
entity |
| Predicate | numberOfEscalatorBanks |
—
|
GENERATED |
| Object | 1 |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfEscalatorBanks Context triple: [Frunzenskaya metro station, numberOfEscalatorBanks, 1]
-
A.
hasNumberOfElevatorBanks
Indicates the relationship specifying how many distinct elevator banks are present in or associated with a given entity.
-
B.
numberOfEscalators
chosen
Indicates the quantity of escalators associated with or present in a given entity or location.
-
C.
hasEscalators
Indicates that one entity is equipped with or contains escalators that can be used for movement between different levels or areas.
-
D.
numberOfElevators
Indicates the total count of elevators associated with a given entity or location.
-
E.
hasEscalatorDepthRank
Indicates the relative position or level of an escalator within an ordered hierarchy of escalators (e.g., by depth, floor, or sequence).
- F. None of above.
Provenance (1 batch)
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_69f3494c6f9c8190a255409fce8b1d3b |
completed | April 30, 2026, 12:21 p.m. |
Created at: May 1, 2026, 1:22 a.m.