Triple
T7979099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silvaner wine |
E185519
|
entity |
| Predicate | oftenBottledIn |
P80116
|
FINISHED |
| Object | Bocksbeutel bottle |
—
|
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: Bocksbeutel bottle | Statement: [Silvaner wine, oftenBottledIn, Bocksbeutel bottle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenBottledIn Context triple: [Silvaner wine, oftenBottledIn, Bocksbeutel bottle]
-
A.
wineAVA
Indicates that a wine is produced within a specific American Viticultural Area (AVA) designation.
-
B.
madeWithAlcohol
Indicates that something is created, prepared, or produced using alcohol as an ingredient or component.
-
C.
wineLaw
Indicates a legal or regulatory relationship governing the production, sale, labeling, or distribution of wine.
-
D.
wineStructure
Indicates the overall sensory framework of a wine, encompassing how its components like acidity, tannin, body, and alcohol are balanced and interact.
-
E.
offersDistilleryExclusiveBottlings
Indicates that an entity (such as a distillery or retailer) provides bottlings that are available exclusively at the distillery itself.
- 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_69ca829851908190b4e03829353ee7c3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c261904819086910898071f3629 |
completed | March 31, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69cb048009a08190b4c577208a9f8f76 |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14bbbacc81909c6cf8ec35314bbb |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:14 p.m.