Triple

T19856208
Position Surface form Disambiguated ID Type / Status
Subject Le Mortainais E477138 entity
Predicate containsAdministrativeTerritorialEntity P747 FINISHED
Object Barenton 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: Barenton | Statement: [Le Mortainais, containsAdministrativeTerritorialEntity, Barenton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barenton
Context triple: [Le Mortainais, containsAdministrativeTerritorialEntity, Barenton]
  • A. Barenton chosen
    Barenton is a commune in the Manche department of northwestern France, known for its rural character within the Normandy region.
  • B. Noisseville
    Noisseville is a commune in northeastern France, near Metz in the Moselle department, known historically as the site of a major Franco-Prussian War battle.
  • C. Belm
    Belm is a municipality in Lower Saxony, Germany, situated just east of the city of Osnabrück.
  • D. Fullerville
    Fullerville is a historic mill village and former industrial community that is now a notable historic site within Villa Rica, Georgia.
  • E. Tailleville
    Tailleville is a small commune in the Calvados department of the Normandy region in northwestern France.
  • 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_69d8e51e7d948190aedbcd6c30361c39 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6586c14fc81908d34785f1088b0a9 completed April 20, 2026, 4:46 p.m.
Created at: April 10, 2026, 1:51 p.m.