Triple
T23102659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dôle (Pinot Noir–Gamay blend) |
E576073
|
entity |
| Predicate | consumptionWindow |
P150927
|
FINISHED |
| Object | usually drunk young |
—
|
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: usually drunk young | Statement: [Dôle (Pinot Noir–Gamay blend), consumptionWindow, usually drunk young]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: consumptionWindow Context triple: [Dôle (Pinot Noir–Gamay blend), consumptionWindow, usually drunk young]
-
A.
consumptionState
Indicates the current status or condition of how something is being used up, consumed, or depleted.
-
B.
consumedAfter
Indicates that one item is consumed only after another specified item has been consumed.
-
C.
consumedFor
Indicates that one entity is used up, spent, or depleted in order to produce, enable, or obtain another entity.
-
D.
consumes
Indicates that one entity eats, drinks, or otherwise uses up another entity as a resource or nourishment.
-
E.
consumptionMethod
Indicates the manner or process by which something is consumed, used up, or ingested.
- F. None of above. chosen
Provenance (4 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_69e245c060b48190a9bd61a47a16db17 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18de9fa8c81909fd26ff37173b85b |
completed | April 29, 2026, 4:49 a.m. |
| PD | Predicate disambiguation | batch_69ef89e5ce748190b2c3ac3843484127 |
completed | April 27, 2026, 4:08 p.m. |
| PDg | Predicate description generation | batch_69ef9b7494f4819088ae59ea3d0ae8ab |
completed | April 27, 2026, 5:23 p.m. |
Created at: April 17, 2026, 3:58 p.m.