Triple
T17495942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blanquette de Limoux |
E426059
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Limoux |
—
|
NE NERFINISHED |
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: Limoux | Statement: [Blanquette de Limoux, region, Limoux]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Limoux Context triple: [Blanquette de Limoux, region, Limoux]
-
A.
Limoux
chosen
Limoux is a small town in southern France known for its sparkling wine Blanquette de Limoux and its long-running carnival traditions.
-
B.
Céret
Céret is a historic town in southern France near the Spanish border, renowned for its modern art museum and its association with early 20th-century artists like Picasso and Braque.
-
C.
Limoux AOC
Limoux AOC is a renowned French wine appellation in southern Occitanie, best known for its traditional sparkling wines considered among the oldest in the world.
-
D.
Camprodon
Camprodon is a small town in the Catalan Pyrenees of northeastern Spain, known for its scenic mountain setting and historic Romanesque architecture.
-
E.
Cuers
Cuers is a commune in the Var department of southeastern France, situated inland from Toulon in the Provence-Alpes-Côte d’Azur region.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889dccf7481909264a1844a2e9100 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4520e9c8c8190aa955766bc915d26 |
completed | April 19, 2026, 3:54 a.m. |
Created at: April 10, 2026, 5:48 a.m.