Triple
T6089149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KGR |
E135716
|
entity |
| Predicate | registrationPlatePrefixFor |
P7142
|
FINISHED |
| Object | Gorlice area |
—
|
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: Gorlice area | Statement: [KGR, registrationPlatePrefixFor, Gorlice area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: registrationPlatePrefixFor Context triple: [KGR, registrationPlatePrefixFor, Gorlice area]
-
A.
registrationPlateFormat
Indicates the specific pattern or structure that a vehicle’s registration plate must follow (such as the arrangement of letters, numbers, and symbols).
-
B.
isOnLicensePlateBeforeNumber
Indicates that one element appears on a license plate in a position preceding a specified number.
-
C.
firstCharactersOfPlate
Indicates that one entity specifies the initial characters appearing at the beginning of another entity’s license plate identifier.
-
D.
registrationPrefix
chosen
Indicates that an entity has a specific registration prefix code assigned to it as part of its official registration or identification.
-
E.
vehicleRegistrationCode
Indicates the official registration identifier assigned to a vehicle, typically used for legal identification and record-keeping.
- 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_69c0087bcc788190b20f093d3a6c60ec |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057a862c88190912a913973c6b6fc |
completed | March 22, 2026, 8:57 p.m. |
| PD | Predicate disambiguation | batch_69c049f3b1ec8190bea67a7bec6442a5 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:12 p.m.