Triple
T2640154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Côte de Sézanne |
E62844
|
entity |
| Predicate | wineStyleProduced |
P2082
|
FINISHED |
| Object | Champagne base wines |
—
|
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: Champagne base wines | Statement: [Côte de Sézanne, wineStyleProduced, Champagne base wines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wineStyleProduced Context triple: [Côte de Sézanne, wineStyleProduced, Champagne base wines]
-
A.
wineStyle
chosen
Indicates the stylistic category or type of wine (such as its production style, sweetness, body, or other defining characteristics) associated with an entity.
-
B.
wineStructure
Indicates the overall sensory framework of a wine, encompassing how its components like acidity, tannin, body, and alcohol are balanced and interact.
-
C.
wineLaw
Indicates a legal or regulatory relationship governing the production, sale, labeling, or distribution of wine.
-
D.
producesWine
Indicates that one entity creates or manufactures wine as a product.
-
E.
wineExport
Indicates a relationship where one entity exports wine to another entity or destination.
- 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.