Triple
T19467078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Côte Brune |
E487027
|
entity |
| Predicate | grapeStyleContribution |
P102176
|
FINISHED |
| Object | tannic structure |
—
|
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: tannic structure | Statement: [Côte Brune, grapeStyleContribution, tannic structure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grapeStyleContribution Context triple: [Côte Brune, grapeStyleContribution, tannic structure]
-
A.
wineStyleContribution
chosen
Indicates how much a given factor or component influences or shapes the overall style or character of a wine.
-
B.
usesGrapeType
Indicates that one entity employs or incorporates a specific type or variety of grape in its composition, production, or process.
-
C.
grapeSourceFlexibility
Indicates that the source or origin of grapes involved in a relationship or process can vary or be chosen flexibly rather than being fixed.
-
D.
grapeSource
Indicates that one entity is the origin or provider of grapes used by another entity.
-
E.
grapeProduct
Indicates that one entity is a product derived from or made using grapes.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633e2aee081908330a5665fa60482 |
completed | April 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7499a4819082bec0be8afba35c |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:39 p.m.