Triple
T13698021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sestriere |
E328437
|
entity |
| Predicate | hasNearbyResort |
P3449
|
FINISHED |
| Object | Montgenèvre |
E55197
|
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: Montgenèvre | Statement: [Sestriere, hasNearbyResort, Montgenèvre]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montgenèvre Context triple: [Sestriere, hasNearbyResort, Montgenèvre]
-
A.
Montgenèvre
chosen
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.
-
B.
Genolier
Genolier is a small municipality in the canton of Vaud in western Switzerland, known for its scenic setting near Lake Geneva and the Jura Mountains.
-
C.
Gueugnon
Gueugnon is a small commune in eastern France known historically for its steel industry and location in the Bourgogne-Franche-Comté region.
-
D.
Saignelégier
Saignelégier is a municipality in the Swiss canton of Jura known for its rural landscapes, watchmaking heritage, and the annual Marché-Concours horse festival.
-
E.
Faucigny
Faucigny is a historical region in the French Alps that once formed part of the medieval domains of the Counts of Savoy.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc878b57c819094e7ea6d1a64211f |
completed | April 12, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fbac7c8bbc81908c7aa15c6892be34 |
completed | May 6, 2026, 9:02 p.m. |
Created at: April 9, 2026, 9:54 p.m.