Triple
T4630043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vigneux-sur-Seine |
E101390
|
entity |
| Predicate | hasDemonym |
P191
|
FINISHED |
| Object | Vigneusienne |
E457627
|
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: Vigneusienne | Statement: [Vigneux-sur-Seine, hasDemonym, Vigneusienne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vigneusienne Context triple: [Vigneux-sur-Seine, hasDemonym, Vigneusienne]
-
A.
Vigneusien
chosen
Vigneusien is the French demonym for an inhabitant of the commune of Vigneux-sur-Seine in the Île-de-France region.
-
B.
Vauvert
Vauvert is a commune in southern France known for its location in the Gard department near the Camargue region.
-
C.
Auberjonois
Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
-
D.
Le Vigan
Le Vigan is a historic market town in southern France that serves as one of the main gateways to the Cévennes mountain region.
-
E.
Brionnais
Brionnais is a historic rural region in eastern France known for its Romanesque churches, traditional stone villages, and Charolais cattle farming.
- 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a316ef48190831970ec914cf5a2 |
completed | March 20, 2026, 2:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be03652dc081908abc3e036f853edf |
completed | March 21, 2026, 2:33 a.m. |
Created at: March 20, 2026, 1:13 p.m.