Triple
T10491119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AOC |
E247418
|
entity |
| Predicate | notableExample |
P1503
|
FINISHED |
| Object | Roquefort AOC |
E162264
|
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: Roquefort AOC | Statement: [AOC, notableExample, Roquefort AOC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roquefort AOC Context triple: [AOC, notableExample, Roquefort AOC]
-
A.
Roquefort
chosen
Roquefort is a famous French blue cheese made from sheep's milk and aged in the natural caves of Roquefort-sur-Soulzon.
-
B.
Rocamadour cheese
Rocamadour cheese is a small, soft, creamy goat’s milk cheese from France’s Lot region, prized for its delicate flavor and traditional production.
-
C.
Fourme d'Ambert
Fourme d'Ambert is a traditional French blue cheese from the Auvergne region, known for its cylindrical shape, mild creamy flavor, and protected designation of origin (PDO) status.
-
D.
Langres cheese
Langres cheese is a soft, washed-rind cow’s milk cheese from the Champagne region of France, known for its cylindrical shape with a sunken top and strong, tangy flavor.
-
E.
Mont d'Or cheese
Mont d'Or cheese is a soft, rich, washed-rind cow’s milk cheese from the Jura region of France, traditionally sold in a spruce-wood box and eaten warm and spoonable.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5097d61e08190952d4354ef1bce52 |
completed | April 7, 2026, 1:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8dca37b0881908ced885d9853bc1b |
completed | April 10, 2026, 11:18 a.m. |
Created at: April 6, 2026, 12:24 p.m.