Triple
T20075993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GJ-18 |
E499863
|
entity |
| Predicate | vehicleIdentifierRole |
P70937
|
FINISHED |
| Object | regional identifier on license plates |
—
|
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: regional identifier on license plates | Statement: [GJ-18, vehicleIdentifierRole, regional identifier on license plates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleIdentifierRole Context triple: [GJ-18, vehicleIdentifierRole, regional identifier on license plates]
-
A.
vehicleIdentificationRole
chosen
Indicates a role in which an entity serves to identify, label, or distinguish a vehicle within a given context or system.
-
B.
vehicleName
Indicates the specific name or designation assigned to a vehicle.
-
C.
intendedVehicle
Indicates that one entity is the vehicle that another entity plans or is meant to use.
-
D.
vehicleType
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
E.
vehicleUsed
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6643bcfd48190893abd3734f15cd3 |
completed | April 20, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 3:40 p.m.