Triple
T34626032
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beaunoir |
E889138
|
entity |
| Predicate | hasViticulturalRole |
P42428
|
FINISHED |
| Object | historical grape variety |
—
|
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: historical grape variety | Statement: [Beaunoir, hasViticulturalRole, historical grape variety]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasViticulturalRole Context triple: [Beaunoir, hasViticulturalRole, historical grape variety]
-
A.
viticulturalRole
chosen
Indicates the specific function, responsibility, or involvement an entity has within viticulture or grape-growing activities.
-
B.
hasVineyards
Indicates that one entity possesses, contains, or is associated with vineyards used for growing grapevines.
-
C.
hasViticulturalImportance
Indicates that something plays a significant role or has notable relevance in the cultivation and production of grapes for wine.
-
D.
hasVineyardType
Indicates the specific type or classification of a vineyard associated with an entity.
-
E.
hasWinemakingFocus
Indicates that an entity is specifically oriented toward, specialized in, or primarily concerned with winemaking activities or practices.
- 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_69f349d64a388190a013cfa9bd33fad7 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd37b695c88190855801626f91c4cd |
completed | May 8, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69fd374cccf08190a230e87164af5938 |
completed | May 8, 2026, 1:07 a.m. |
Created at: May 1, 2026, 2:04 a.m.