Triple
T14815785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francs Côtes de Bordeaux AOC |
E348309
|
entity |
| Predicate | typicalWhiteWineStyle |
P2082
|
FINISHED |
| Object | dry white wine |
—
|
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: dry white wine | Statement: [Francs Côtes de Bordeaux AOC, typicalWhiteWineStyle, dry white wine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWhiteWineStyle Context triple: [Francs Côtes de Bordeaux AOC, typicalWhiteWineStyle, dry white wine]
-
A.
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.
-
B.
wineVariety
Indicates the specific type or variety of wine associated with an entity.
-
C.
traditionalWineChoice
Indicates that an entity selects or prefers a wine option that aligns with customary or historically established pairing or serving practices.
-
D.
whiteWineShare
Indicates the proportion or share of white wine within a larger set, such as total wine consumption, production, or sales.
-
E.
wineStylesAssociatedWith
Indicates a relationship where certain wine styles are linked or connected to a particular entity, such as a region, grape, producer, or product.
- 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_69d822eb8f588190bf53445e730a934f |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decfe2c1ec81908b3dff7a5d0e85d0 |
completed | April 14, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69de8c0ef8a4819092d84478b1f56db1 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:49 a.m.