Triple
T23102511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Petite Arvine |
E576069
|
entity |
| Predicate | acidityContributionToWine |
P102176
|
FINISHED |
| Object | freshness |
—
|
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: freshness | Statement: [Petite Arvine, acidityContributionToWine, freshness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: acidityContributionToWine Context triple: [Petite Arvine, acidityContributionToWine, freshness]
-
A.
wineAcidityType
Indicates the type or category of acidity associated with a given wine.
-
B.
wineStyleContribution
chosen
Indicates how much a given factor or component influences or shapes the overall style or character of a wine.
-
C.
oenologicalSignificance
Indicates the relationship in which something holds importance, relevance, or notable impact within the context of wine or winemaking.
-
D.
vinificationUse
Indicates the process or method of winemaking applied to a given wine or batch.
-
E.
wineCharacteristic
Indicates a descriptive property or quality attributed to a wine, such as its flavor, aroma, color, or style.
- 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_69e245c060b48190a9bd61a47a16db17 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18de9fa8c81909fd26ff37173b85b |
completed | April 29, 2026, 4:49 a.m. |
| PD | Predicate disambiguation | batch_69ef89e5ce748190b2c3ac3843484127 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 3:58 p.m.