Triple
T3769847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CO |
E82769
|
entity |
| Predicate | isOnLicensePlateBeforeNumber |
P51042
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [CO, isOnLicensePlateBeforeNumber, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOnLicensePlateBeforeNumber Context triple: [CO, isOnLicensePlateBeforeNumber, true]
-
A.
firstCharactersOfPlate
Indicates that one entity specifies the initial characters appearing at the beginning of another entity’s license plate identifier.
-
B.
hasPlate
Indicates that one entity possesses, is equipped with, or includes a plate as part of its attributes or components.
-
C.
licensePlateSystem
Indicates a system or scheme used to assign, format, and manage license plate identifiers for vehicles.
-
D.
previouslyLicensedAs
Indicates that an entity held a license under a different name or status at some earlier time.
-
E.
plateNumberOf
Indicates the license plate number that is assigned to or associated with a particular vehicle.
- 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_69ad8b207b0081909d2b48843fbd8795 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc2f016c81909c2e3c85dbc3c259 |
completed | March 8, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69adc04ec36c8190bd5b944d4f4d32aa |
completed | March 8, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69adc133ef50819094c2b971f31f1615 |
completed | March 8, 2026, 6:34 p.m. |
Created at: March 8, 2026, 3:35 p.m.