Triple
T680037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prévessin-Moëns |
E13160
|
entity |
| Predicate | hasDemonym |
P191
|
FINISHED |
| Object | Prévessinoise |
E13160
|
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: Prévessinoise | Statement: [Prévessin-Moëns, hasDemonym, Prévessinoise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prévessinoise Context triple: [Prévessin-Moëns, hasDemonym, Prévessinoise]
-
A.
Mâconnais
Mâconnais is a wine-producing subregion in southern Burgundy, France, best known for its Chardonnay-based white wines.
-
B.
Chêne-Bourg
Chêne-Bourg is a municipality in western Switzerland located in the canton of Geneva, forming part of the Geneva metropolitan area near the French border.
-
C.
Prévessin-Moëns
chosen
Prévessin-Moëns is a French commune in the Ain department of eastern France, located near Geneva and known for its proximity to the CERN research center.
-
D.
Chêne-Bougeries
Chêne-Bougeries is a suburban municipality in western Switzerland, located just east of the city of Geneva in the canton of Geneva.
-
E.
Montgenèvre
Montgenèvre is a French Alpine ski resort village in the Hautes-Alpes department, known for its high-altitude slopes and location near the Italian border.
- 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_69a4933d3bf88190972041cd8cf143b9 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a04f4efc819082767a7517fa760a |
completed | March 1, 2026, 8:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5dc9f5f7c8190a766c6b545d1abd8 |
completed | March 2, 2026, 6:53 p.m. |
Created at: March 1, 2026, 7:36 p.m.