Triple

T95774
Position Surface form Disambiguated ID Type / Status
Subject Alps region E1926 entity
Predicate highestPoint P210 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: [Alps region, highestPoint, Mont Blanc]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mont Blanc
Context triple: [Alps region, highestPoint, 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. Mount Elbrus
    Mount Elbrus is a dormant stratovolcano in the Caucasus Mountains of Russia and the highest peak on the European continent.
  • C. Aconcagua
    Aconcagua is the highest mountain in the Americas and the tallest peak outside of Asia, located in the Andes of western Argentina.
  • D. Gran Glaciar Norte
    Gran Glaciar Norte is the largest and most prominent glacier on Mexico’s Pico de Orizaba volcano, forming a major part of its high-altitude ice cap.
  • E. Ben Nevis
    Ben Nevis is the tallest mountain in the British Isles, located near Fort William in the Scottish Highlands and popular for hiking and climbing.
  • 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_69a24d4862f881908cc8b89d3a78031d completed Feb. 28, 2026, 2:04 a.m.
NER Named-entity recognition batch_69a24fd4777c81909ea9b9a6bd4f7ad5 completed Feb. 28, 2026, 2:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a266ed314881908b6e5e7a91930b56 completed Feb. 28, 2026, 3:54 a.m.
Created at: Feb. 28, 2026, 2:09 a.m.