Triple

T4665701
Position Surface form Disambiguated ID Type / Status
Subject Miage range E102839 entity
Predicate near P350 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: [Miage range, near, Mont Blanc]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mont Blanc
Context triple: [Miage range, near, 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_69bd43d9cba4819086c1ab1c2d9d2133 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd633c3ea08190b8a66afbba1dcb1c completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69be0384a1488190a59dc08766f526dd completed March 21, 2026, 2:33 a.m.
Created at: March 20, 2026, 1:15 p.m.