Triple
T18502364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bozel |
E452107
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | La Plagne |
—
|
NE NERFINISHED |
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: La Plagne | Statement: [Bozel, near, La Plagne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Plagne Context triple: [Bozel, near, La Plagne]
-
A.
La Plagne
chosen
La Plagne is a major French Alpine ski resort renowned for its extensive slopes and role as a venue during the 1992 Albertville Winter Olympics.
-
B.
Tignes
Tignes is a high-altitude ski resort and alpine commune in the French Alps, renowned for its extensive ski area and year-round glacier skiing.
-
C.
Val-d’Isère
Val-d’Isère is a renowned French Alpine ski resort village famous for its extensive slopes and role as a host venue for major international skiing competitions.
-
D.
Flaine
Flaine is a purpose-built French Alpine ski resort in the Grand Massif area, known for its extensive slopes and modernist architecture.
-
E.
Valloire
Valloire is a French Alpine village and ski resort in the Savoie department, known for its mountain scenery and proximity to major cycling climbs.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d3855d50819097fc8561b0299dd9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e532c535908190bdc90c58fc5bdaf7 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 11:36 a.m.