Triple
T7817117
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DF |
E181037
|
entity |
| Predicate | partOfVehicleRegistrationSystem |
P18660
|
FINISHED |
| Object | Brazilian vehicle registration system |
—
|
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: Brazilian vehicle registration system | Statement: [DF, partOfVehicleRegistrationSystem, Brazilian vehicle registration system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfVehicleRegistrationSystem Context triple: [DF, partOfVehicleRegistrationSystem, Brazilian vehicle registration system]
-
A.
vehicleRegistrationCode
Indicates the official registration identifier assigned to a vehicle, typically used for legal identification and record-keeping.
-
B.
licensePlateSystem
chosen
Indicates a system or scheme used to assign, format, and manage license plate identifiers for vehicles.
-
C.
registrationNumber
Indicates the unique identifier assigned to an entity as part of an official or formal registration process.
-
D.
identifiesVehiclesRegisteredIn
Indicates that an entity specifies or determines which vehicles are registered within a particular scope or authority.
-
E.
vehicleRegistrationCategory
Indicates the classification or type of registration assigned to a vehicle under a specific regulatory or administrative scheme.
- 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_69ca828153f48190bdb27ac46f8e0745 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf96ea6d881908eff5f750e0f6700 |
completed | March 30, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69cae91687788190af9cb7aaa996d291 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:39 p.m.