Triple
T31041856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canterbury wine region |
E791014
|
entity |
| Predicate | primaryWineColour |
—
|
GENERATED |
| Object | red wine |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryWineColour Context triple: [Canterbury wine region, primaryWineColour, red wine]
-
A.
wineColor
chosen
Indicates the color attribute or hue associated with a given wine.
-
B.
wineColorMajority
Indicates that the majority of a given set or collection of wines share the same color.
-
C.
wineColorOptions
Indicates the set of possible color categories that can be associated with a given wine.
-
D.
grapeColorForRosé
Indicates that a particular grape color is used in the production of rosé wine.
-
E.
primaryGrapeVariety
Indicates that one entity is the main or predominant grape variety used in producing the other entity (typically a wine or wine-based product).
- F. None of above.
Provenance (1 batch)
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_69f224ca2fa881908a3ac5fedf207b90 |
completed | April 29, 2026, 3:33 p.m. |
Created at: April 29, 2026, 8:59 p.m.