Triple

T348090
Position Surface form Disambiguated ID Type / Status
Subject Cabernet Franc E6983 entity
Predicate notableAppellation P12667 FINISHED
Object Fronsac E51137 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: Fronsac | Statement: [Cabernet Franc, notableAppellation, Fronsac]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fronsac
Context triple: [Cabernet Franc, notableAppellation, Fronsac]
  • A. Fronsac chosen
    Fronsac is a French wine appellation on the right bank of the Dordogne River, known for its Merlot-based red wines and proximity to Bordeaux.
  • B. Côtes de Bourg
    Côtes de Bourg is a French wine appellation on the right bank of the Gironde estuary known for producing robust, Merlot-dominant red wines within the Bordeaux region.
  • C. Montluçon
    Montluçon is a historic industrial town in central France known for its medieval old quarter and role as a key urban center in the Allier department.
  • D. Châteauroux
    Châteauroux is a city in central France that will host the shooting events for the 2024 Summer Olympics.
  • E. Bordeaux
    Bordeaux is a renowned wine-producing region in southwestern France, famous for its prestigious red blends and long winemaking tradition.
  • 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_69a2e7951ba08190960e90823b5078f3 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2ee043fac8190af72291c04761687 completed Feb. 28, 2026, 1:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69a44f5030f481908af8aa1d361b8124 completed March 1, 2026, 2:38 p.m.
Created at: Feb. 28, 2026, 1:08 p.m.