Triple
T20243763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Clape AOC |
E498367
|
entity |
| Predicate | styleWhiteWine |
P2082
|
FINISHED |
| Object | aromatic |
—
|
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: aromatic | Statement: [La Clape AOC, styleWhiteWine, aromatic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: styleWhiteWine Context triple: [La Clape AOC, styleWhiteWine, aromatic]
-
A.
whiteWineShare
Indicates the proportion or share of white wine within a larger set, such as total wine consumption, production, or sales.
-
B.
wineStyle
chosen
Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
-
C.
wineColor
Indicates the color attribute or hue associated with a given wine.
-
D.
sweetWineSuitability
Indicates the degree to which something is appropriate or recommended for pairing with or serving as a sweet wine.
-
E.
wineStyleContribution
Indicates how much a given factor or component influences or shapes the overall style or character of a wine.
- 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e67170aa248190922fc845d2265ae3 |
completed | April 20, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69e55b1b23f88190bdcbe2f81dd226dd |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:40 p.m.