Triple
T11131469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château Malartic-Lagravière |
E263292
|
entity |
| Predicate | typicalWhiteBlendDominantGrape |
P975
|
FINISHED |
| Object | Sauvignon Blanc |
—
|
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: Sauvignon Blanc | Statement: [Château Malartic-Lagravière, typicalWhiteBlendDominantGrape, Sauvignon Blanc]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalWhiteBlendDominantGrape Context triple: [Château Malartic-Lagravière, typicalWhiteBlendDominantGrape, Sauvignon Blanc]
-
A.
primaryGrapeVariety
chosen
Indicates that one entity is the main or predominant grape variety used in producing the other entity (typically a wine or wine-based product).
-
B.
traditionalGrapeVariety
Indicates that a grape variety is traditionally or historically used in a specific region, wine style, or cultural winemaking practice.
-
C.
typicalViognierPercentage
Indicates the usual proportion of Viognier used within a given wine, blend, or production context.
-
D.
whiteWineProductionAllowed
Indicates that producing white wine is permitted under the relevant rules, regulations, or conditions.
-
E.
whiteWineShare
Indicates the proportion or share of white wine within a larger set, such as total wine consumption, production, or sales.
- 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_69d6aa9c0ba08190bbd19c217489b755 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e831f4808190afabdaa0e97bbe32 |
completed | April 9, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69d75ce104908190b6cc31ef2f67846a |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.