Triple
T13909692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valtournenche |
E334454
|
entity |
| Predicate | hasNotablePeakVisible |
P112249
|
FINISHED |
| Object | Dent d’Hérens |
E167381
|
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: Dent d’Hérens | Statement: [Valtournenche, hasNotablePeakVisible, Dent d’Hérens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dent d’Hérens Context triple: [Valtournenche, hasNotablePeakVisible, Dent d’Hérens]
-
A.
Dent d'Hérens
chosen
Dent d'Hérens is a prominent alpine peak on the Swiss-Italian border, located near the Matterhorn in the Pennine Alps.
-
B.
Dent de Crolles
Dent de Crolles is a prominent limestone peak in the French Alps known for its extensive cave systems and panoramic views over the Chartreuse region.
-
C.
Dent de Morcles
Dent de Morcles is a prominent mountain in the western Swiss Alps overlooking the Rhône Valley, known for its striking limestone cliffs and panoramic views.
-
D.
Val-Cenis
Val-Cenis is a French Alpine commune and ski resort area in the Savoie department, known for its mountain landscapes and winter sports tourism.
-
E.
Longjumeau
Longjumeau is a suburban commune in the southern outskirts of Paris, France, known for its residential character and proximity to major transport routes.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2aa428ac819084e7c4b244d15f20 |
completed | April 14, 2026, 11:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7d44d848190ab445833e64a6bfc |
completed | May 7, 2026, 8:36 p.m. |
Created at: April 9, 2026, 10:16 p.m.