Triple
T2640164
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Côte de Sézanne |
E62844
|
entity |
| Predicate | wineRegionClassification |
P8842
|
FINISHED |
| Object | appellation within Champagne AOC |
—
|
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: appellation within Champagne AOC | Statement: [Côte de Sézanne, wineRegionClassification, appellation within Champagne AOC]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineRegionClassification Context triple: [Côte de Sézanne, wineRegionClassification, appellation within Champagne AOC]
-
A.
wineClassificationSystem
Indicates a system or scheme used to categorize and organize wines based on defined criteria such as origin, style, or quality.
-
B.
wineRegion
Indicates the geographical region or area where a particular wine is produced or originates.
-
C.
appellationType
Indicates the specific kind or category of name or designation applied to an entity.
-
D.
wineGrapesCultivated
Indicates that certain grape varieties are grown or cultivated specifically for producing wine.
-
E.
wineRegionPartOf
chosen
Indicates that a wine-producing region is geographically or administratively contained within a larger wine region or area.
- 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_69ab4c3f2dcc819082df80f5e032f690 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abd8fc8ee881908a9f6820d8934a62 |
completed | March 7, 2026, 7:51 a.m. |
| PD | Predicate disambiguation | batch_69abd812849881908f956845a80e0205 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.