Triple
T5004150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Côte-Rôtie |
E112445
|
entity |
| Predicate | maximumViognierPercentage |
P61432
|
FINISHED |
| Object | 20% |
—
|
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: 20% | Statement: [Côte-Rôtie, maximumViognierPercentage, 20%]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumViognierPercentage Context triple: [Côte-Rôtie, maximumViognierPercentage, 20%]
-
A.
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).
-
B.
minimumMalbecPercentage
Indicates the minimum required percentage of Malbec in a composition, blend, or product for a given rule or classification to apply.
-
C.
grapeVarietyAllowed
Indicates that a specific grape variety is permitted or authorized for use in a given context, such as a wine, region, or product specification.
-
D.
grapeMinimum
Indicates the minimum quantity, size, or threshold value associated with grapes in a given context.
-
E.
whiteWineProductionAllowed
Indicates that producing white wine is permitted under the relevant rules, regulations, or conditions.
- F. None of above. chosen
Provenance (4 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_69bd4433d0b08190877e83959ef40d81 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd7472a1dc8190942f568a81fdd961 |
completed | March 20, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69bd714aee2481908fb0dd5fa2daf3a1 |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd74713fc88190916c2b04cd2e677e |
completed | March 20, 2026, 4:23 p.m. |
Created at: March 20, 2026, 1:35 p.m.