Triple

T21905668
Position Surface form Disambiguated ID Type / Status
Subject Livradois-Forez Regional Natural Park E540930 entity
Predicate locatedInAdministrativeTerritory P40 FINISHED
Object Allier NE NERFINISHED

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: Allier | Statement: [Livradois-Forez Regional Natural Park, locatedInAdministrativeTerritory, Allier]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Allier
Context triple: [Livradois-Forez Regional Natural Park, locatedInAdministrativeTerritory, Allier]
  • A. Allier chosen
    Allier is a major river in central France that flows northward through the Massif Central before joining the Loire.
  • B. Arpitanie
    Arpitanie is a cultural and linguistic region in parts of France, Switzerland, and Italy where the Arpitan (Franco-Provençal) language and related traditions are historically rooted.
  • C. L’Union
    L’Union is a French regional newspaper known for covering local and national news in the Champagne-Ardenne and surrounding areas.
  • D. L’Union
    L’Union is a suburban commune in southwestern France, located just northeast of Toulouse and integrated into its metropolitan area.
  • E. Franca
    Franca is a city in the northeastern part of the Brazilian state of São Paulo, known historically for its leather and footwear industry.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c47b4e8c81908c8076eaa4c8e4f2 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f121d62a648190af7074251dc6a03a completed April 28, 2026, 9:08 p.m.
Created at: April 16, 2026, 7:35 p.m.