Triple

T12487884
Position Surface form Disambiguated ID Type / Status
Subject Charente E298483 entity
Predicate subprefecture P9697 FINISHED
Object Cognac E300144 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: Cognac | Statement: [Charente, subprefecture, Cognac]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cognac
Context triple: [Charente, subprefecture, Cognac]
  • A. Cognac chosen
    Cognac is a renowned French town in the Charente department, famous worldwide as the center of production for the eponymous brandy.
  • B. Branson Cognac
    Branson Cognac is a premium cognac brand associated with rapper and entrepreneur 50 Cent, known for its luxury positioning in the spirits market.
  • C. Armagnac
    Armagnac is a historic French brandy-producing region renowned for its distinctive, long-aged eaux-de-vie made from local grapes.
  • D. Calvados
    Calvados is a department in the Normandy region of northwestern France, known for its historic D-Day landing beaches and production of the apple brandy that shares its name.
  • E. Hennessy
    Hennessy is a surname most prominently associated with John L. Hennessy, a renowned computer scientist and former president of Stanford University.
  • 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_69d6ada377208190a36011199a4d8558 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94de077bc81908b5ff057a1bf2b4f completed April 10, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f64ba7d8bc8190acc1f0d537a5bbbb completed May 2, 2026, 7:08 p.m.
Created at: April 8, 2026, 9:56 p.m.