Triple
T38490412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montgomery City Lines |
E918038
|
entity |
| Predicate | operatedVehicleUsedIn |
—
|
GENERATED |
| Object | Rosa Parks arrest |
—
|
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: operatedVehicleUsedIn Context triple: [Montgomery City Lines, operatedVehicleUsedIn, Rosa Parks arrest]
-
A.
usedAsVehicleFor
Indicates that one entity functions as a means of transportation or conveyance for another entity.
-
B.
vehicleUsed
chosen
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
-
C.
usedAsReleaseVehicleFor
Indicates that one entity is employed as the means or mechanism to launch, distribute, or deliver another entity.
-
D.
hasVehicularUse
Indicates that something is used for, intended for, or associated with operation by vehicles or vehicular traffic.
-
E.
wasKeyVehicleIn
Indicates that a vehicle played a central or decisive role in a specified event, situation, or outcome.
- 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_69f76e9894208190a129a553a60ca58c |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:31 p.m.