Triple
T10300592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château La Tour-Martillac |
E241616
|
entity |
| Predicate | primaryRedBlendStyle |
P55208
|
FINISHED |
| Object | Cabernet Sauvignon–Merlot–Petit Verdot blend |
—
|
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: Cabernet Sauvignon–Merlot–Petit Verdot blend | Statement: [Château La Tour-Martillac, primaryRedBlendStyle, Cabernet Sauvignon–Merlot–Petit Verdot blend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryRedBlendStyle Context triple: [Château La Tour-Martillac, primaryRedBlendStyle, Cabernet Sauvignon–Merlot–Petit Verdot blend]
-
A.
wineStyle
Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
-
B.
primaryGrapeVariety
Indicates that one entity is the main or predominant grape variety used in producing the other entity (typically a wine or wine-based product).
-
C.
grapeColorForReds
Indicates that the predicate specifies the typical color of grapes used to produce red wines.
-
D.
wineColor
Indicates the color attribute or hue associated with a given wine.
-
E.
wineStylesAssociatedWith
chosen
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_69d381aaafc08190af475ef58dc16aba |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2eefe8881908a672c4dca7657ca |
completed | April 7, 2026, 9:48 a.m. |
| PD | Predicate disambiguation | batch_69d4d1f35e548190be3b4d92d65d2d20 |
completed | April 7, 2026, 9:44 a.m. |
Created at: April 6, 2026, 11:44 a.m.