Triple

T10081373
Position Surface form Disambiguated ID Type / Status
Subject Merseburg E213906 entity
Predicate hasTwinTown P919 FINISHED
Object Châtillon, France E664659 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: Châtillon, France | Statement: [Merseburg, hasTwinTown, Châtillon, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Châtillon, France
Context triple: [Merseburg, hasTwinTown, Châtillon, France]
  • A. Fourchambault, France
    Fourchambault, France is a small industrial town in the Nièvre department of central France, historically known for its steelworks and metallurgical industry.
  • B. Châtillon
    Châtillon is a suburban commune in the southwestern outskirts of Paris, France, known for its residential character and integration into the Greater Paris metropolitan area.
  • C. Châtillon chosen
    Châtillon is a commune in eastern France known for its local heritage and its twinning partnership with the Swiss town of Delémont.
  • D. Pontchâteau, France
    Pontchâteau is a commune in western France’s Loire-Atlantique department, known for its historic religious sites and its location between Nantes and Vannes.
  • E. Châtillon-sur-Seine
    Châtillon-sur-Seine is a historic commune in eastern France’s Côte-d’Or department, known for its rich archaeological heritage and picturesque setting along the Seine River.
  • 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_69ca839bf730819086900c323c9b8c95 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd032ef288190a961d266d9ecafbc completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2b660987c8190a6a29d9e56acbff7 completed April 5, 2026, 7:22 p.m.
Created at: March 30, 2026, 9 p.m.