Triple
T2048678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Côte Chalonnaise |
E45512
|
entity |
| Predicate | grapeVariety |
P975
|
FINISHED |
| Object | Gamay |
E45511
|
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: Gamay | Statement: [Côte Chalonnaise, grapeVariety, Gamay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gamay Context triple: [Côte Chalonnaise, grapeVariety, Gamay]
-
A.
Gamay
chosen
Gamay is a red wine grape variety best known for producing light, fruity wines, particularly in France’s Beaujolais region.
-
B.
Valleiry
Valleiry is a small French commune in the Haute-Savoie department of the Auvergne-Rhône-Alpes region in southeastern France, near the Swiss border.
-
C.
Huelén
Huelén is the former indigenous name for Cerro Santa Lucía, a historic hill and urban park in central Santiago, Chile.
-
D.
Vaudesir
Vaudésir is one of the prestigious Grand Cru vineyard sites in the Chablis wine region of Burgundy, renowned for producing some of its most refined and age-worthy Chardonnay wines.
-
E.
Sauvy
Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
- 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_69a8891948208190ab7898da21824c77 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb98c70c48190beb98aad56d9daf1 |
completed | March 7, 2026, 5:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae2007386481908b46c7bc2db8e4dd |
completed | March 9, 2026, 1:19 a.m. |
Created at: March 4, 2026, 7:39 p.m.