Triple
T5548067
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bezirk Frankfurt (Oder) |
E145457
|
entity |
| Predicate | hadVehicleRegistrationCode |
P1173
|
FINISHED |
| Object | F |
—
|
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: F | Statement: [Bezirk Frankfurt (Oder), hadVehicleRegistrationCode, F]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadVehicleRegistrationCode Context triple: [Bezirk Frankfurt (Oder), hadVehicleRegistrationCode, F]
-
A.
vehicleRegistrationCode
chosen
Indicates the official registration identifier assigned to a vehicle, typically used for legal identification and record-keeping.
-
B.
hasHistoricRegistrationPlateCode
Indicates that an entity is associated with a specific code assigned to its historic (vintage/classic) vehicle registration plate.
-
C.
registrationNumber
Indicates the unique identifier assigned to an entity as part of an official or formal registration process.
-
D.
hasVehicle
Indicates that one entity possesses, owns, or is assigned a vehicle.
-
E.
hasPlate
Indicates that one entity possesses, is equipped with, or includes a plate as part of its attributes or components.
- 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_69c008fb879c81909f5bfa56fadc1d46 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fe0244c8190aeb995f79f22a039 |
completed | March 22, 2026, 4:59 p.m. |
| PD | Predicate disambiguation | batch_69c01b0e72f08190bf705d8fe1639401 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:35 p.m.