Triple

T3795166
Position Surface form Disambiguated ID Type / Status
Subject Gard E89752 entity
Predicate subprefecture P9697 FINISHED
Object Le Vigan E275524 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: Le Vigan | Statement: [Gard, subprefecture, Le Vigan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Le Vigan
Context triple: [Gard, subprefecture, Le Vigan]
  • A. Le Vigan chosen
    Le Vigan is a historic market town in southern France that serves as one of the main gateways to the Cévennes mountain region.
  • B. Vavin
    Vavin is a Paris Métro station in the 6th arrondissement, serving the Montparnasse and Jardin du Luxembourg area.
  • C. Crevel
    Crevel is a vain, wealthy former perfumer and libertine in Honoré de Balzac’s novel "La Cousine Bette," emblematic of the corrupt bourgeois society he satirizes.
  • D. Juliénas
    Juliénas is a French wine appellation in the northern Beaujolais region, known for its structured, aromatic red wines primarily made from the Gamay grape.
  • E. Viré
    Viré is a renowned wine-producing village in France’s Mâconnais region, best known for its high-quality white Burgundy wines made primarily from Chardonnay.
  • 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_69aed9597d6881909b6ee3b9de859223 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee79db2e88190b3aa2b8e8d885e19 completed March 9, 2026, 3:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f05c0f908190b5638e75b06dab4d completed March 14, 2026, 5:21 a.m.
Created at: March 9, 2026, 3:15 p.m.