Triple
T30995256
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tresallier |
E789778
|
entity |
| Predicate | wineProfileAcidity |
P56868
|
FINISHED |
| Object | high acidity |
—
|
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: high acidity | Statement: [Tresallier, wineProfileAcidity, high acidity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineProfileAcidity Context triple: [Tresallier, wineProfileAcidity, high acidity]
-
A.
wineAcidityType
chosen
Indicates the type or category of acidity associated with a given wine.
-
B.
sparklingWineSweetnessRange
Indicates the range of sweetness levels that a sparkling wine can have or is classified within.
-
C.
wineCharacteristic
Indicates a descriptive property or quality attributed to a wine, such as its flavor, aroma, color, or style.
-
D.
wineStyleContribution
Indicates how much a given factor or component influences or shapes the overall style or character of a wine.
-
E.
wineStructure
Indicates the overall sensory framework of a wine, encompassing how its components like acidity, tannin, body, and alcohol are balanced and interact.
- 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_69f224c65a348190baaed1c01a29900c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6953bafb88190a860e9c68a3dd4b2 |
completed | May 3, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69f690ef92308190903a54fc74233269 |
completed | May 3, 2026, 12:03 a.m. |
Created at: April 29, 2026, 8:56 p.m.