Triple
T9386420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graves Supérieures |
E225915
|
entity |
| Predicate | typicalAlcoholByVolumeRange |
P69107
|
FINISHED |
| Object | 12–14% ABV |
—
|
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: 12–14% ABV | Statement: [Graves Supérieures, typicalAlcoholByVolumeRange, 12–14% ABV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalAlcoholByVolumeRange Context triple: [Graves Supérieures, typicalAlcoholByVolumeRange, 12–14% ABV]
-
A.
alcoholType
Indicates the specific kind or category of alcohol associated with an entity (e.g., beer, wine, spirits).
-
B.
bottlingStrengthRange
chosen
Indicates the range of alcohol strengths at which a beverage is bottled.
-
C.
isAlcoholicBeverage
Indicates that a beverage contains alcohol and is classified as an alcoholic drink.
-
D.
madeWithAlcohol
Indicates that something is created, prepared, or produced using alcohol as an ingredient or component.
-
E.
servesAlcohol
Indicates that an establishment or provider offers and supplies alcoholic beverages to customers or participants.
- 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_69ca842e9dcc8190a264119e683cfe04 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd50d3964c8190b0353f56df755db8 |
completed | April 1, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_69cca53bd6ec81909bf403ce304e5c08 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:45 p.m.