Triple
T879836
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mont Blanc massif |
E19000
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Chamonix |
E12797
|
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: Chamonix | Statement: [Mont Blanc massif, near, Chamonix]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chamonix Context triple: [Mont Blanc massif, near, Chamonix]
-
A.
Chamonix
chosen
Chamonix is a renowned French alpine town and ski resort in the Haute-Savoie region, famous for its dramatic mountain scenery and mountaineering history.
-
B.
Bourg-Saint-Maurice
Bourg-Saint-Maurice is a French Alpine town in the Savoie department, known as a gateway to major ski resorts such as Les Arcs in the Graian Alps.
-
C.
Aiguilles de Chamonix
Aiguilles de Chamonix are a dramatic cluster of sharp granite peaks in the Mont Blanc massif of the French Alps, renowned worldwide for alpine climbing and mountaineering.
-
D.
Crans-Montana
Crans-Montana is a renowned Swiss Alpine resort town known for its skiing, golf courses, and panoramic views of the Valais Alps.
-
E.
La Clusaz
La Clusaz is a well-known French Alpine village and ski resort renowned for its extensive slopes and traditional mountain charm.
- 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_69a4939c32488190a7ccd41cf0abb22b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4acc9d5f4819087afbb75b6ac3dbf |
completed | March 1, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac537700548190aa8ead8c966eb329 |
completed | March 7, 2026, 4:33 p.m. |
Created at: March 1, 2026, 7:39 p.m.