Triple

T12603645
Position Surface form Disambiguated ID Type / Status
Subject Brienne dynasty E300918 entity
Predicate associatedPlace P1481 FINISHED
Object Brienne-le-Château E45039 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: Brienne-le-Château | Statement: [Brienne dynasty, associatedPlace, Brienne-le-Château]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brienne-le-Château
Context triple: [Brienne dynasty, associatedPlace, Brienne-le-Château]
  • A. Brienne-le-Château chosen
    Brienne-le-Château is a commune in northeastern France best known as the town where Napoleon Bonaparte attended military school in his youth.
  • B. Magnicourt
    Magnicourt is a small French commune located in the Aube department in the Grand Est region of northeastern France.
  • C. Château de Brienne
    Château de Brienne is a historic French castle in the town of Brienne-le-Château, notably associated with Napoleon Bonaparte’s early military education.
  • D. Châteaurenault
    Châteaurenault was a notable 17th-century French naval officer and admiral who played a key role in several major maritime conflicts of his time.
  • E. Courcouronnes
    Courcouronnes is a suburban commune in the southern Île-de-France region of France, located in the Essonne department near Paris.
  • 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954e6e20481908bca684c4b497c48 completed April 10, 2026, 7:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65ecb09e481909d688f174372dde7 completed May 2, 2026, 8:30 p.m.
Created at: April 9, 2026, 5:10 p.m.