Triple
T3864638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buick Envision |
E91821
|
entity |
| Predicate | modelYearsNorthAmerica |
P4161
|
FINISHED |
| Object | 2016–present |
—
|
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: 2016–present | Statement: [Buick Envision, modelYearsNorthAmerica, 2016–present]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modelYearsNorthAmerica Context triple: [Buick Envision, modelYearsNorthAmerica, 2016–present]
-
A.
modelYearLaunchForNorthAmerica
Indicates the year a model was first launched specifically for the North American market.
-
B.
modelYears
chosen
Indicates the association between a product (often a vehicle or device) and the specific calendar years in which that model version was produced or marketed.
-
C.
productionYears
Indicates the span of calendar years during which something was produced or manufactured.
-
D.
yearFirstDelivered
Indicates the calendar year in which something (such as a product, service, or item) was first delivered or made available.
-
E.
lastAppearanceYear
Indicates the calendar year in which an entity made its most recent appearance.
- 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_69aed9645f348190a9868e7cef56ab7e |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec3871d881909c6c8e6d08203801 |
completed | March 9, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69aee754dddc8190936e1f9c40a770db |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.