Triple
T2582387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pinot Meunier |
E57121
|
entity |
| Predicate | typicalUseInChampagne |
P40414
|
FINISHED |
| Object | adds fruitiness |
—
|
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: adds fruitiness | Statement: [Pinot Meunier, typicalUseInChampagne, adds fruitiness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalUseInChampagne Context triple: [Pinot Meunier, typicalUseInChampagne, adds fruitiness]
-
A.
sparklingWineAllowed
Indicates that the use, serving, or presence of sparkling wine is permitted in the given context or under specified conditions.
-
B.
hasChampagneBar
Indicates that an entity includes, features, or is equipped with a champagne bar.
-
C.
appellationType
Indicates the specific kind or category of name or designation applied to an entity.
-
D.
wineServingSuggestion
Indicates the recommended way or context in which a particular wine is best served or enjoyed.
-
E.
notableAppellation
Indicates that an entity is known by, or commonly referred to with, a particular notable name or title.
- 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3c9d0548190b29743ac1d7837ff |
completed | March 7, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69abd0cfeae08190aed03866ba071c5c |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd209d934819093600889af9104c3 |
completed | March 7, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:49 p.m.