Triple
T16246078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cinsault |
E394373
|
entity |
| Predicate | hasTypicalAlcoholLevel |
P2071
|
FINISHED |
| Object | moderate |
—
|
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: moderate | Statement: [Cinsault, hasTypicalAlcoholLevel, moderate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalAlcoholLevel Context triple: [Cinsault, hasTypicalAlcoholLevel, moderate]
-
A.
alcoholLevel
chosen
Indicates the measured concentration or amount of alcohol present in an entity (such as a person, substance, or environment).
-
B.
isAlcoholicBeverage
Indicates that a beverage contains alcohol and is classified as an alcoholic drink.
-
C.
regulatesAlcoholLevel
Indicates a relationship where one entity controls, adjusts, or maintains the alcohol level of another entity or system.
-
D.
alcoholType
Indicates the specific kind or category of alcohol associated with an entity (e.g., beer, wine, spirits).
-
E.
madeWithAlcohol
Indicates that something is created, prepared, or produced using alcohol as an ingredient or component.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24561d250819096f709ea8751fcb9 |
completed | April 17, 2026, 2:36 p.m. |
| PD | Predicate disambiguation | batch_69e219ee6f6481909663b388dc99770a |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.