Triple
T9571579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WUN |
E230932
|
entity |
| Predicate | appliesToTypeOfVehicleRegistration |
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: [WUN, appliesToTypeOfVehicleRegistration, motor vehicles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesToTypeOfVehicleRegistration Context triple: [WUN, appliesToTypeOfVehicleRegistration, 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.
identifiesVehiclesRegisteredIn
Indicates that an entity specifies or determines which vehicles are registered within a particular scope or authority.
-
C.
vehicleRegistrationCategory
Indicates the classification or type of registration assigned to a vehicle under a specific regulatory or administrative scheme.
-
D.
supportsVehicle
Indicates that one entity provides the necessary strength, stability, or structure to bear the weight of a vehicle.
-
E.
appliesToTransportMode
Indicates that a rule, condition, or characteristic is specifically associated with and relevant to a particular mode of transport.
- 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_69ca847f22188190a56e4a97625bef22 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd998bf20881909fad48ecb16dfa31 |
completed | April 1, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69ccd59b960c8190966a8870a2426bd5 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:04 p.m.