Triple
T24994248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pionersky |
E625524
|
entity |
| Predicate | regionalVehicleCode |
P3820
|
FINISHED |
| Object | 39 |
—
|
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: 39 | Statement: [Pionersky, regionalVehicleCode, 39]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionalVehicleCode Context triple: [Pionersky, regionalVehicleCode, 39]
-
A.
countryVehicleRegistrationSystem
Indicates a relationship where a country maintains or governs an official system for registering vehicles within its jurisdiction.
-
B.
vehicleRegistrationCode
Indicates the official registration identifier assigned to a vehicle, typically used for legal identification and record-keeping.
-
C.
chassisCode
Indicates the specific chassis designation or code assigned to a vehicle model to distinguish its underlying structural platform or variant.
-
D.
regionCodeType
chosen
Indicates the classification or format type used for a given region code within a coding or identification system.
-
E.
identifiesVehiclesRegisteredIn
Indicates that an entity specifies or determines which vehicles are registered within a particular scope or authority.
- 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_69e2ff2611c081908710457fbe6d376b |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f657f653448190a945b4751af8507d |
completed | May 2, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 18, 2026, 6:04 a.m.