Triple

T5524140
Position Surface form Disambiguated ID Type / Status
Subject Montbrison E144882 entity
Predicate locatedNear P294 FINISHED
Object Monts du Forez E9424 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 du Forez | Statement: [Montbrison, locatedNear, Monts du Forez]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monts du Forez
Context triple: [Montbrison, locatedNear, Monts du Forez]
  • A. Cévennes
    The Cévennes is a rugged mountainous region in south-central France known for its dramatic landscapes, chestnut forests, and historical role as a refuge for Protestant Huguenots.
  • B. Monts du Lyonnais
    Monts du Lyonnais is a hilly, rural massif in eastern France known for its scenic landscapes, small villages, and agricultural countryside west of Lyon.
  • C. Morvan Massif
    The Morvan Massif is a heavily forested highland region in central France known for its rounded granite hills, lakes, and protected natural landscapes.
  • D. Massif Central chosen
    The Massif Central is a vast highland region in south-central France characterized by ancient volcanic mountains, plateaus, and deep river valleys.
  • E. Montagne Noire
    Montagne Noire is a mountain range in southern France known for its forested slopes, rich water resources, and role as a key watershed feeding regional rivers and canals.
  • 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_69c008f873a481909b4d9f7e2db3c37d completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f85c8508190a0a089402b49a04f completed March 22, 2026, 4:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027f6aa1c8190b639c317c7d60f64 completed March 22, 2026, 5:33 p.m.
Created at: March 22, 2026, 3:34 p.m.