Triple
T35929761
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PL |
E1039125
|
entity |
| Predicate | usedAsVehicleRegistrationCode |
P173473
|
FINISHED |
| Object | PL |
—
|
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: PL | Statement: [PL, usedAsVehicleRegistrationCode, PL]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsVehicleRegistrationCode Context triple: [PL, usedAsVehicleRegistrationCode, PL]
-
A.
vehicleRegistrationCode
Indicates the official registration identifier assigned to a vehicle, typically used for legal identification and record-keeping.
-
B.
appliesToVehicleRegistration
Indicates that something (such as a rule, fee, document, or condition) is relevant or applicable to a specific vehicle registration.
-
C.
usedAsVehicleFor
Indicates that one entity functions as a means of transportation or conveyance for another entity.
-
D.
carNumberUsed
Indicates that a specific car number has been used or assigned in a given context or event.
-
E.
vehicleCode
chosen
Indicates a relationship where a specific code or identifier is assigned to or associated with a vehicle.
- 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_69f76e23e4688190a5369138755138bf |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69feba0f09508190b3e871c62b19ec7f |
completed | May 9, 2026, 4:37 a.m. |
| PD | Predicate disambiguation | batch_69feb957fe7c8190969fb31a6d1a59c8 |
completed | May 9, 2026, 4:34 a.m. |
Created at: May 3, 2026, 4:07 p.m.