Triple
T5065862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pila |
E114142
|
entity |
| Predicate | hasViewOf |
P854
|
FINISHED |
| Object | Mont Blanc |
E2386
|
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: Mont Blanc | Statement: [Pila, hasViewOf, Mont Blanc]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mont Blanc Context triple: [Pila, hasViewOf, Mont Blanc]
-
A.
Mont Blanc
chosen
Mont Blanc is the tallest mountain in the Alps and Western Europe, straddling the border between France and Italy and renowned for mountaineering and skiing.
-
B.
Montenvers
Montenvers is a mountain station and viewpoint in the French Alps above Chamonix, best known as the access point to the Mer de Glace glacier.
-
C.
Mont Blanc du Tacul
Mont Blanc du Tacul is a prominent 4,248-meter peak in the Mont Blanc massif of the French Alps, popular with mountaineers as part of the classic route to Mont Blanc.
-
D.
Monte Rosa
Monte Rosa is a prominent massif in the Pennine Alps on the border between Switzerland and Italy, known for being the second-highest mountain in the Alps and Western Europe.
-
E.
Aiguille du Dru
Aiguille du Dru is a striking granite peak in the Mont Blanc massif of the French Alps, famed among climbers for its steep faces and challenging 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_69bd443c0c8c81908663b77afb28e165 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd749aceac8190817278266308fd64 |
completed | March 20, 2026, 4:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bea49d917081909ead17eed3f8af90 |
completed | March 21, 2026, 2:01 p.m. |
Created at: March 20, 2026, 1:38 p.m.