Triple
T13018985
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camargue cowboys |
E322626
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Camargue |
E10340
|
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: Camargue | Statement: [Camargue cowboys, region, Camargue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Camargue Context triple: [Camargue cowboys, region, Camargue]
-
A.
Camargue
chosen
Camargue is a vast wetland region in southern France known for its salt marshes, wild white horses, black bulls, and rich birdlife including flamingos.
-
B.
Port Camargue
Port Camargue is a large Mediterranean marina in southern France, known as one of Europe’s biggest pleasure-boat harbors and a major center for nautical tourism.
-
C.
Dombes
Dombes is a historic rural region in eastern France known for its many ponds, wetlands, and traditional fish farming.
-
D.
Montpellier plain
The Montpellier plain is a low-lying area surrounding the city of Montpellier in southern France, characterized by its agricultural landscapes and Mediterranean climate.
-
E.
Béziers plain
The Béziers plain is a fertile lowland region in southern France known for its vineyards, agriculture, and proximity to the Mediterranean coast.
- 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_69d807657e8c8190bd9435ee2f823845 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97ece22908190a0941e23df7c774d |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c116423881908d0de1e04904fbc3 |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 9, 2026, 8:51 p.m.