Triple
T22435090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Val Montjoie |
E554599
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Le Fayet |
—
|
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: Le Fayet | Statement: [Val Montjoie, contains, Le Fayet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Le Fayet Context triple: [Val Montjoie, contains, Le Fayet]
-
A.
Le Fayet
chosen
Le Fayet is a village in the French Alps that serves as a gateway and lower terminus for the historic Tramway du Mont-Blanc mountain railway.
-
B.
La Frenais
La Frenais is a surname most notably associated with British television writer Ian La Frenais, known for co-creating several classic UK comedy series.
-
C.
Antoine-François Peyre
Antoine-François Peyre was an 18th-century French architect and influential teacher associated with the neoclassical movement.
-
D.
Pierre-Étienne
Pierre-Étienne is a French masculine given name, often associated with notable historical and political figures in France.
-
E.
Augereau
Augereau is a French surname most notably borne by Pierre Augereau, a marshal of France during the Napoleonic era.
- 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_69e11e5010e48190ae1e9c9db9697637 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15adda0e48190825a5b705ae52d5b |
completed | April 29, 2026, 1:11 a.m. |
Created at: April 16, 2026, 8:47 p.m.