Triple
T2841002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Côte des Blancs |
E62465
|
entity |
| Predicate | grapeVarietyMinor |
P39767
|
FINISHED |
| Object | Meunier |
E283734
|
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: Meunier | Statement: [Côte des Blancs, grapeVarietyMinor, Meunier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Meunier Context triple: [Côte des Blancs, grapeVarietyMinor, Meunier]
-
A.
Meunier
chosen
Meunier is a black grape variety primarily used in Champagne production, valued for adding fruitiness and early maturity to sparkling wine blends.
-
B.
Meunier
Meunier is a common French occupational surname, historically referring to a miller.
-
C.
Ganthier
Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
-
D.
Firmin
Firmin is a French given name notably borne by Firmin Didot, a renowned printer, typefounder, and member of the influential Didot family in the history of typography.
-
E.
Lebrun
Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
- 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_69ab4c3d16bc81908b3a1c98fbd287fe |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abe08ae5048190a0a3b573d9a5fdbc |
completed | March 7, 2026, 8:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe8d22e588190b119e7d9f9c3873a |
completed | March 10, 2026, 9:48 a.m. |
Created at: March 6, 2026, 10:01 p.m.