Triple

T10709087
Position Surface form Disambiguated ID Type / Status
Subject Vienne River E252485 entity
Predicate flowsThrough P225 FINISHED
Object Chauvigny E683119 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: Chauvigny | Statement: [Vienne River, flowsThrough, Chauvigny]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chauvigny
Context triple: [Vienne River, flowsThrough, Chauvigny]
  • A. Chauvigny chosen
    Chauvigny is a historic town in western France known for its medieval fortifications and picturesque setting in the Vienne department of the Nouvelle-Aquitaine region.
  • B. Verrières
    Verrières is a small French commune located within the Thiers arrondissement in the Puy-de-Dôme department of central France.
  • C. Viry-Châtillon
    Viry-Châtillon is a suburban commune in the southern outskirts of Paris, France, known for its residential character and location along the Seine River in the Essonne department.
  • D. Potigny
    Potigny is a commune in the Calvados department of the Normandy region in northwestern France.
  • E. Souvigny
    Souvigny is a historic town in central France known for its important Cluniac priory and medieval religious heritage.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fe5063bc8190ba12fd68a59c9a03 completed April 9, 2026, 1:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d6878a54819080050011e718c4e8 completed April 18, 2026, 12:55 a.m.
Created at: April 8, 2026, 9:13 p.m.