Triple
T8528115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Tâche AOC |
E201870
|
entity |
| Predicate | wineRegion |
P6176
|
FINISHED |
| Object | Bourgogne |
E6890
|
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: Bourgogne | Statement: [La Tâche AOC, wineRegion, Bourgogne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bourgogne Context triple: [La Tâche AOC, wineRegion, Bourgogne]
-
A.
Burgundy
Burgundy is a mid-level membership tier in the Privilege Club loyalty program, offering enhanced benefits and rewards to frequent participants.
-
B.
Burgundy
chosen
Burgundy is a renowned wine-producing region in eastern France, famous for its high-quality Chardonnay and Pinot Noir wines.
-
C.
Mâconnais
Mâconnais is a wine-producing subregion in southern Burgundy, France, best known for its Chardonnay-based white wines.
-
D.
Côte Chalonnaise
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.
-
E.
Vendômois
Vendômois is the French demonym referring to inhabitants or natives of the town of Vendôme in central France.
- 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_69ca83228b24819085d22e7dc99f5d94 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe672e0588190a84328e1bf974f08 |
completed | March 31, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cea854e8c881909c62b29d999edde8 |
completed | April 2, 2026, 5:33 p.m. |
Created at: March 30, 2026, 6:17 p.m.