Triple
T38689410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ROW |
E949215
|
entity |
| Predicate | appliesToTypeOfVehicle |
P23423
|
FINISHED |
| Object | motor 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: motor vehicles | Statement: [ROW, appliesToTypeOfVehicle, motor vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToTypeOfVehicle Context triple: [ROW, appliesToTypeOfVehicle, motor 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.
usedByVehicleType
Indicates that something (such as a resource, component, or facility) is utilized or operated by a specific type or category of vehicle.
-
C.
appliesToVehicleRegistration
Indicates that something (such as a rule, fee, document, or condition) is relevant or applicable to a specific vehicle registration.
-
D.
supportsVehicle
Indicates that one entity provides the necessary strength, stability, or structure to bear the weight of a vehicle.
-
E.
vehicleEligibility
Indicates whether a given vehicle satisfies the required conditions or criteria to be considered eligible for a specified purpose or program.
- 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_69f76efe16148190befd5dd59c3dfeaa |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69ffe12ee59c8190bc7da386e6d5332d |
completed | May 10, 2026, 1:36 a.m. |
| PD | Predicate disambiguation | batch_69ffe0a138bc8190a3d4b48cd579e985 |
completed | May 10, 2026, 1:34 a.m. |
Created at: May 3, 2026, 4:33 p.m.