Triple
T10628929
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bouzeron |
E250397
|
entity |
| Predicate | regulatesWineType |
P95069
|
FINISHED |
| Object | still white wine only |
—
|
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 white wine only | Statement: [Bouzeron, regulatesWineType, still white wine only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regulatesWineType Context triple: [Bouzeron, regulatesWineType, still white wine only]
-
A.
usesWineType
Indicates that one entity makes use of, incorporates, or is associated with a particular type or category of wine.
-
B.
wineVariety
Indicates the specific type or variety of wine associated with an entity.
-
C.
sparklingWineAllowed
Indicates that the use, serving, or presence of sparkling wine is permitted in the given context or under specified conditions.
-
D.
wineRegulationBody
Indicates that a regulatory organization has authority over the production, labeling, or distribution standards for a particular wine or wine-producing region.
-
E.
hasWineryType
Indicates the specific category or classification of winery associated with an entity.
- 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_69d6aa5993448190a493b790b8f85010 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6df92f8388190a8bcff96809d8eb4 |
completed | April 8, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69d6dd7fae088190973f70c69738af49 |
completed | April 8, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69d6df463ea8819091d6683e476b4f21 |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 8, 2026, 8:59 p.m.