Triple
T1998432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aligoté |
E43409
|
entity |
| Predicate | cultivatedIn |
P2078
|
FINISHED |
| Object | Côte Chalonnaise |
E45512
|
NE 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: Côte Chalonnaise | Statement: [Aligoté, cultivatedIn, Côte Chalonnaise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Côte Chalonnaise Context triple: [Aligoté, cultivatedIn, Côte Chalonnaise]
-
A.
Côte Chalonnaise
chosen
Côte Chalonnaise is a wine-producing subregion of Burgundy in eastern France, known for its value-driven red and white wines primarily from Pinot Noir and Chardonnay.
-
B.
Mâconnais
Mâconnais is a wine-producing subregion in southern Burgundy, France, best known for its Chardonnay-based white wines.
-
C.
Côte de Nuits
Côte de Nuits is a renowned subregion of Burgundy in eastern France, famous for producing some of the world’s finest and most age-worthy red wines.
-
D.
Côte des Bar
Côte des Bar is a southern Champagne-producing area in France known for its rolling hills, Kimmeridgian soils, and Pinot Noir–dominant sparkling wines.
-
E.
Burgundy
Burgundy is a renowned wine-producing region in eastern France, famous for its high-quality Chardonnay and Pinot Noir wines.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a88715dbbc8190b2299e29e955d997 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb867c49081909a9ca5fa21bf7aa3 |
completed | March 7, 2026, 5:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae033e733c8190aa11e316e01dbd17 |
completed | March 8, 2026, 11:16 p.m. |
Created at: March 4, 2026, 7:37 p.m.