Triple

T11954244
Position Surface form Disambiguated ID Type / Status
Subject Saint-Flour E284509 entity
Predicate historicalProvince P915 FINISHED
Object Haute-Auvergne E213603 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: Haute-Auvergne | Statement: [Saint-Flour, historicalProvince, Haute-Auvergne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haute-Auvergne
Context triple: [Saint-Flour, historicalProvince, Haute-Auvergne]
  • A. Auvergne chosen
    Auvergne is a historic region in central France known for its volcanic landscapes, rural character, and Romanesque heritage.
  • B. Livradois-Forez
    Livradois-Forez is a mountainous natural and regional park area in central France known for its forests, rural landscapes, and traditional villages within the Auvergne region.
  • C. Rouergue
    Rouergue is a historic cultural region in southern France, centered around the present-day Aveyron department and known for its rural landscapes, medieval towns, and Occitan heritage.
  • D. Touraine
    Touraine is a historic region in central France, famed for its Loire Valley châteaux, wine production, and role as a former royal heartland.
  • E. Auvergnat
    Auvergnat is a variety of the Occitan language traditionally spoken in France’s Auvergne region and surrounding areas.
  • 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_69d6ab2db38c8190b1f0ed6663ef8ada completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90365da288190a132703df563de23 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63edbcd288190b491a16f2bf8fc62 completed May 2, 2026, 6:13 p.m.
Created at: April 8, 2026, 9:45 p.m.