Triple
T6312136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bezirk Erfurt |
E141527
|
entity |
| Predicate | usedVehicleRegistrationCode |
P1173
|
FINISHED |
| Object | E |
—
|
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: E | Statement: [Bezirk Erfurt, usedVehicleRegistrationCode, E]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedVehicleRegistrationCode Context triple: [Bezirk Erfurt, usedVehicleRegistrationCode, E]
-
A.
vehicleRegistrationCode
chosen
Indicates the official registration identifier assigned to a vehicle, typically used for legal identification and record-keeping.
-
B.
registrationNumber
Indicates the unique identifier assigned to an entity as part of an official or formal registration process.
-
C.
hasHistoricRegistrationPlateCode
Indicates that an entity is associated with a specific code assigned to its historic (vintage/classic) vehicle registration plate.
-
D.
vehicleUsed
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
-
E.
primaryCarNumberUsed
Indicates that a particular car number is the main or default one used for an entity in a given context.
- 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_69c008d00efc8190a36c05b4b4a3bf4b |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0649ea98c819086509e175812c6c0 |
completed | March 22, 2026, 9:52 p.m. |
| PD | Predicate disambiguation | batch_69c060e311b48190b1c74a5cf9435623 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:28 p.m.