Triple

T12521731
Position Surface form Disambiguated ID Type / Status
Subject Monts Dore volcanic field E299334 entity
Predicate mountainRange P648 FINISHED
Object Monts Dore E56438 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: Monts Dore | Statement: [Monts Dore volcanic field, mountainRange, Monts Dore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monts Dore
Context triple: [Monts Dore volcanic field, mountainRange, Monts Dore]
  • A. Monts Dore chosen
    Monts Dore is a volcanic mountain range in central France known for its ancient stratovolcano, high plateaus, and popular hiking and winter sports areas.
  • B. Bois du Cazier
    Bois du Cazier is a former coal mine in Marcinelle, Belgium, now preserved as a museum and memorial site best known for the 1956 mining disaster that killed 262 miners.
  • C. Montet
    Montet is a French surname most notably borne by archaeologist Pierre Montet, renowned for his discoveries in the royal necropolis of Tanis in Egypt.
  • D. Montmorency plateau
    The Montmorency plateau is a raised geographic area in the Val-d'Oise department of northern France, known for its suburban communities overlooking the Paris metropolitan region.
  • E. Les Montets
    Les Montets is a small municipality in the canton of Fribourg in western Switzerland.
  • 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_69d6ada5cdd48190860d9ce30aff69be completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d9545b2b2481909049a490c97678f2 completed April 10, 2026, 7:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a535943081909f893b2be006cc28 completed May 3, 2026, 1:30 a.m.
Created at: April 8, 2026, 9:57 p.m.