Triple

T23220733
Position Surface form Disambiguated ID Type / Status
Subject Duke of Nevers E580881 entity
Predicate governedFrom P6175 FINISHED
Object Nevers (city) 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: Nevers (city) | Statement: [Duke of Nevers, governedFrom, Nevers (city)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nevers (city)
Context triple: [Duke of Nevers, governedFrom, Nevers (city)]
  • A. Nevers chosen
    Nevers is a historic city in central France known for its medieval architecture, religious heritage, and traditional faience pottery.
  • B. Toul
    Toul is a historic commune in northeastern France known for its medieval fortifications and impressive Gothic cathedral.
  • C. Tournus
    Tournus is a historic town in eastern France’s Burgundy region, known for its Romanesque abbey and riverside setting along the Saône.
  • D. Villefranche-sur-Saône
    Villefranche-sur-Saône is a commune in eastern France that serves as the principal town of the Beaujolais region and a key urban center north of Lyon.
  • E. City of Nancy
    The City of Nancy is a historic city in northeastern France renowned for its elegant 18th-century architecture and UNESCO-listed squares.
  • 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_69e2460389408190be74f41d217799a9 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1916870148190853874e6cf26bbc7 completed April 29, 2026, 5:04 a.m.
Created at: April 17, 2026, 4:08 p.m.