Triple

T8848525
Position Surface form Disambiguated ID Type / Status
Subject Gascogne E210572 entity
Predicate traditionalProduct P3553 FINISHED
Object Armagnac E206235 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: Armagnac | Statement: [Gascogne, traditionalProduct, Armagnac]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Armagnac
Context triple: [Gascogne, traditionalProduct, Armagnac]
  • A. Armagnac chosen
    Armagnac is a historic French brandy-producing region renowned for its distinctive, long-aged eaux-de-vie made from local grapes.
  • B. Cognac
    Cognac is a renowned French town in the Charente department, famous worldwide as the center of production for the eponymous brandy.
  • C. 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.
  • 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_69ca838967bc8190b46c3c80a2887ea4 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60aa6db0819097c3257499200afc completed April 1, 2026, 12:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf89c6788881908d6f5c49434b556d completed April 3, 2026, 9:35 a.m.
Created at: March 30, 2026, 6:49 p.m.