Triple
T16506288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calabar Municipal Local Government Area |
E400938
|
entity |
| Predicate | hasVehiclePlateCodePrefix |
P68833
|
FINISHED |
| Object | CR |
—
|
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: CR | Statement: [Calabar Municipal Local Government Area, hasVehiclePlateCodePrefix, CR]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVehiclePlateCodePrefix Context triple: [Calabar Municipal Local Government Area, hasVehiclePlateCodePrefix, CR]
-
A.
hasVehicleLicensePrefix
chosen
Indicates that one entity has, uses, or is associated with a specific vehicle license plate prefix represented by the other entity.
-
B.
hasStationCodePrefix
Indicates that one entity’s station code begins with the prefix specified by the other entity.
-
C.
usesCodeOnPlates
Indicates that an entity applies or employs a specific code or coding system on plates.
-
D.
isOnLicensePlateBeforeNumber
Indicates that one element appears on a license plate in a position preceding a specified number.
-
E.
hasAirportCodePrefix
Indicates that an airport’s code begins with a specified sequence of characters.
- 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_69d88381f6148190819958a038be990e |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e52a2b48190ae715e7db0fd3aad |
completed | April 18, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69e296902d6c8190884ddb612b8c5b36 |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:14 a.m.