Triple
T22106451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liaoyuan |
E546298
|
entity |
| Predicate | vehicleLicensePrefix |
P68833
|
FINISHED |
| Object | 吉D |
—
|
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: 吉D | Statement: [Liaoyuan, vehicleLicensePrefix, 吉D]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleLicensePrefix Context triple: [Liaoyuan, vehicleLicensePrefix, 吉D]
-
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.
isOnLicensePlateBeforeNumber
Indicates that one element appears on a license plate in a position preceding a specified number.
-
C.
roadNumberPrefix
Indicates that one entity is a prefix portion of the road number or designation used by the other entity.
-
D.
licensePlateLocation
Indicates the physical position or placement of a license plate on or relative to an object or vehicle.
-
E.
licensePlateOrigin
Indicates that a vehicle’s license plate was issued or originates from a particular jurisdiction or region.
- 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12919dd388190b8ca08e2464cb0b8 |
completed | April 28, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69e71b2ed7348190b6fa2e52f54393fb |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:30 p.m.