Triple
T15973413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adventure City |
E387378
|
entity |
| Predicate | hasAssociatedVehicleType |
P23423
|
FINISHED |
| Object | rescue vehicles |
—
|
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: rescue vehicles | Statement: [Adventure City, hasAssociatedVehicleType, rescue vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedVehicleType Context triple: [Adventure City, hasAssociatedVehicleType, rescue vehicles]
-
A.
appliedToVehicleType
chosen
Indicates that something (such as a rule, restriction, or condition) is specifically applicable to a particular type or category of vehicle.
-
B.
hasVehicle
Indicates that one entity possesses, owns, or is assigned a vehicle.
-
C.
hasVehicularUse
Indicates that something is used for, intended for, or associated with operation by vehicles or vehicular traffic.
-
D.
hasCabType
Indicates that an entity is associated with or characterized by a specific type or category of cab.
-
E.
hasVehicleCollection
Indicates that an entity possesses or maintains a set or collection of vehicles.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142d6fb588190b4176eab4bbae774 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:54 a.m.