Triple

T19799547
Position Surface form Disambiguated ID Type / Status
Subject Creuse E475633 entity
Predicate capital P234 FINISHED
Object Guéret 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: Guéret | Statement: [Creuse, capital, Guéret]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guéret
Context triple: [Creuse, capital, Guéret]
  • A. Guéret chosen
    Guéret is a small city in central France that serves as the capital of the Creuse department in the Nouvelle-Aquitaine region.
  • B. Montluçon
    Montluçon is a historic industrial town in central France known for its medieval old quarter and role as a key urban center in the Allier department.
  • C. Chapeauroux
    Chapeauroux is a river in central France that flows through the Massif Central before joining the Allier.
  • D. Beaucaire
    Beaucaire is a historic town in southern France known for its medieval architecture and its location along the Rhône River.
  • E. Aurillac
    Aurillac is a historic town in south-central France, known as the capital of the Cantal department and for its traditional umbrella-making 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_69d8e51b014081908b263e167370529a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e653c930a08190a2263db7170edd71 completed April 20, 2026, 4:26 p.m.
Created at: April 10, 2026, 1:49 p.m.