Triple
T6112674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rhône river basin |
E136282
|
entity |
| Predicate | hasMouthNear |
P350
|
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: [Rhône river basin, hasMouthNear, Camargue]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Camargue Context triple: [Rhône river basin, hasMouthNear, 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.
Ver-sur-Mer
Ver-sur-Mer is a coastal village in Normandy, France, known for its location on Gold Beach, one of the key Allied landing sectors during the D-Day invasion of World War II.
-
E.
Libatique
Libatique is the surname of Matthew Libatique, an acclaimed American cinematographer known for his work on films such as "Black Swan" and "Requiem for a Dream."
- 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_69c0089ea6f88190b349be53e04b4f5f |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05bbde2048190909aa3a8097bcf93 |
completed | March 22, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c125631e008190921206b9e355202b |
completed | March 23, 2026, 11:34 a.m. |
Created at: March 22, 2026, 4:13 p.m.