Triple
T11391380
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mont Veyrier |
E269845
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Bornes Massif |
E925844
|
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: Bornes Massif | Statement: [Mont Veyrier, partOf, Bornes Massif]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bornes Massif Context triple: [Mont Veyrier, partOf, Bornes Massif]
-
A.
Bornes Massif
chosen
Bornes Massif is a limestone mountain range in the French Alps, known for its rugged peaks and scenic hiking areas near Lake Annecy.
-
B.
Écrins massif
The Écrins massif is a prominent mountain range in the French Alps known for its high, glaciated peaks and inclusion within the protected Écrins National Park.
-
C.
Massif des Bauges
Massif des Bauges is a limestone mountain range and regional natural park in the French Alps, known for its rugged peaks, forests, and traditional alpine villages.
-
D.
Montagne Noire
Montagne Noire is a mountain range in southern France known for its forested slopes, rich water resources, and role as a key watershed feeding regional rivers and canals.
-
E.
Chartreuse Massif
Chartreuse Massif is a prominent limestone mountain range in southeastern France, known for its dramatic cliffs, deep gorges, and the Carthusian monastery that inspired the Chartreuse liqueur.
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d8001796f48190822526f52e3f0337 |
completed | April 9, 2026, 7:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6e7580c508190a81eadd9015c75ef |
completed | April 21, 2026, 2:56 a.m. |
Created at: April 8, 2026, 9:34 p.m.