Triple
T17495982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blanquette de Limoux |
E426059
|
entity |
| Predicate | wineLawFramework |
P38943
|
FINISHED |
| Object | French AOC system |
—
|
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: French AOC system | Statement: [Blanquette de Limoux, wineLawFramework, French AOC system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineLawFramework Context triple: [Blanquette de Limoux, wineLawFramework, French AOC system]
-
A.
countryWineLawFramework
Indicates the legal and regulatory framework a country has established to govern the production, classification, distribution, and sale of wine.
-
B.
wineLaw
chosen
Indicates a legal or regulatory relationship governing the production, sale, labeling, or distribution of wine.
-
C.
wineRegulationBody
Indicates that a regulatory organization has authority over the production, labeling, or distribution standards for a particular wine or wine-producing region.
-
D.
wineRegulationStatus
Indicates the regulatory classification or compliance status that applies to a given wine under relevant laws or standards.
-
E.
wineStructure
Indicates the overall sensory framework of a wine, encompassing how its components like acidity, tannin, body, and alcohol are balanced and interact.
- 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_69d889dccf7481909264a1844a2e9100 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4520e9c8c8190aa955766bc915d26 |
completed | April 19, 2026, 3:54 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f5fbcc8190a6ea9639bf5650da |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:48 a.m.