Triple
T6026617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cangzhou |
E134196
|
entity |
| Predicate | hasVehicleLicensePrefix |
P68833
|
FINISHED |
| Object | 冀J |
—
|
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: 冀J | Statement: [Cangzhou, hasVehicleLicensePrefix, 冀J]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVehicleLicensePrefix Context triple: [Cangzhou, hasVehicleLicensePrefix, 冀J]
-
A.
isOnLicensePlateBeforeNumber
Indicates that one element appears on a license plate in a position preceding a specified number.
-
B.
hasLicense
Indicates that an entity possesses a valid authorization or permit, typically granted by an authority, to perform a specific activity or use something.
-
C.
cityOfLicense
Indicates the city in which an entity (typically a broadcast station or similar regulated service) is officially licensed or authorized to operate.
-
D.
typeOfLicense
Indicates the specific kind or category of license associated with an entity.
-
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. chosen
Provenance (4 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_69c0087515148190a97475d412563865 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0560cdc308190b25ca8ecb42c4e4f |
completed | March 22, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69c049e75b3881908be106fbcf8c68d4 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8c5bfc8190b986a7071d1b23e3 |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:07 p.m.