Triple
T618867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glacier des Bossons |
E14465
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Les Houches |
E69658
|
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: Les Houches | Statement: [Glacier des Bossons, near, Les Houches]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Les Houches Context triple: [Glacier des Bossons, near, Les Houches]
-
A.
Les Houches
chosen
Les Houches is a French Alpine village and ski resort near Chamonix, known for its family-friendly slopes and World Cup downhill course.
-
B.
Modane
Modane is a French Alpine town in the Savoie department known as a key transit point through the Fréjus Road and Rail Tunnels between France and Italy.
-
C.
Limoges
Limoges is a historic city in central France renowned for its fine porcelain production and medieval architecture.
-
D.
Boncourt
Boncourt is a locality known for its historic Château de Boncourt, reflecting its cultural and architectural heritage.
-
E.
Vichy
Vichy is a spa town in central France renowned for its thermal springs, health resorts, and role as the seat of the World War II Vichy regime.
- 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e25956c8190a1eed87002548658 |
completed | March 1, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a55a79a0488190a9d22229ea97e5ec |
completed | March 2, 2026, 9:38 a.m. |
Created at: March 1, 2026, 7:35 p.m.