Triple

T21426154
Position Surface form Disambiguated ID Type / Status
Subject Forez province E528558 entity
Predicate hasDemonym P191 FINISHED
Object Forézienne 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: Forézienne | Statement: [Forez province, hasDemonym, Forézienne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Forézienne
Context triple: [Forez province, hasDemonym, Forézienne]
  • A. Forézien chosen
    Forézien is the French demonym for inhabitants of the historical Forez province in central France.
  • B. Verdunois
    Verdunois is a regional dialect of the Lorrain Romance language traditionally spoken around the area of Verdun in northeastern France.
  • C. Vieussan
    Vieussan is a small commune in southern France’s Hérault department, known for its scenic setting along the Orb River amid rugged, wine-growing countryside.
  • D. Vivarois
    Vivarois is a Romance dialect of the Occitan language traditionally spoken in parts of southeastern France.
  • E. Vallée de Gaube
    Vallée de Gaube is a scenic glacial valley in the French Pyrenees, renowned for its alpine landscapes, hiking trails, and access to the nearby Lac de Gaube.
  • 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_69e0c455f3688190810bc96365791b0f completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ee813c7a048190a400e364c8df1dcf completed April 26, 2026, 9:18 p.m.
Created at: April 16, 2026, 5:48 p.m.