Triple

T16458687
Position Surface form Disambiguated ID Type / Status
Subject Orcet E399748 entity
Predicate locatedNear P294 FINISHED
Object Clermont-Ferrand E25094 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: Clermont-Ferrand | Statement: [Orcet, locatedNear, Clermont-Ferrand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Clermont-Ferrand
Context triple: [Orcet, locatedNear, Clermont-Ferrand]
  • A. Clermont-Ferrand chosen
    Clermont-Ferrand is a central French city known for its historic cathedral built of black volcanic stone and as the longtime headquarters of the tire company Michelin.
  • B. Rodez
    Rodez is a historic cathedral city in southern France that serves as the capital of the Aveyron department in the Occitanie region.
  • C. Saint-Étienne
    Saint-Étienne is an industrial city in central France known for its historic manufacturing heritage, football culture, and role as one of the host cities for major international sporting events.
  • D. Aix-les-Bains
    Aix-les-Bains is a French spa and resort town in the Savoie department, renowned for its thermal baths and lakeside setting on the edge of the Alps.
  • E. Nantes
    Nantes is a historic port city in western France on the Loire River, known for its maritime heritage, cultural institutions, and vibrant arts scene.
  • 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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32d7ff0e881909100bb5b33c04291 completed April 18, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00cfbbbb888190b750d8f4c005ee42 completed May 10, 2026, 6:34 p.m.
Created at: April 10, 2026, 5:10 a.m.