Triple
T27827695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gutedel wine |
E703002
|
entity |
| Predicate | hasWineStyleVariant |
P95084
|
FINISHED |
| Object | still wine |
—
|
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: still wine | Statement: [Gutedel wine, hasWineStyleVariant, still wine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWineStyleVariant Context triple: [Gutedel wine, hasWineStyleVariant, still wine]
-
A.
wineStylesAssociatedWith
Indicates a relationship where certain wine styles are linked or connected to a particular entity, such as a region, grape, producer, or product.
-
B.
alsoUsesGrapeVariety
Indicates that one entity, in addition to another, makes use of the same grape variety in its composition or production.
-
C.
grapeVarietal
Indicates that one entity is a specific type or variety of grape used in wine or grape production in relation to another entity.
-
D.
wineStyleContribution
Indicates how much a given factor or component influences or shapes the overall style or character of a wine.
-
E.
hasWineCategory
chosen
Indicates that one entity is classified under, or associated with, a particular category or type of wine.
- 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_69ef840ad1e88190b5bff2d1ddec8700 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f67257b0448190a13011af81c81449 |
completed | May 2, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69f66ec3d3d48190ab2f2b71939e572e |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 27, 2026, 5:53 p.m.