Triple
T38490412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montgomery City Lines |
E918038
|
entity |
| Predicate | operatedVehicleUsedIn |
P12443
|
FINISHED |
| Object | Rosa Parks arrest |
—
|
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: Rosa Parks arrest | Statement: [Montgomery City Lines, operatedVehicleUsedIn, Rosa Parks arrest]
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 (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_69f76e9894208190a129a553a60ca58c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a036f0569cc8190a8ac7f4e07145d15 |
completed | May 12, 2026, 6:18 p.m. |
| PD | Predicate disambiguation | batch_6a036c42cf2481908760c7d48b9fc001 |
completed | May 12, 2026, 6:06 p.m. |
Created at: May 3, 2026, 4:31 p.m.