Triple

T11784601
Position Surface form Disambiguated ID Type / Status
Subject Franc-Lyonnais E280238 entity
Predicate borderedBy P224 FINISHED
Object Lyonnais E426772 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: Lyonnais | Statement: [Franc-Lyonnais, borderedBy, Lyonnais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lyonnais
Context triple: [Franc-Lyonnais, borderedBy, Lyonnais]
  • A. Lyonnais chosen
    Lyonnais is a historical region in east-central France centered around the city of Lyon, known for its rich cultural heritage, gastronomy, and role as a major economic hub.
  • B. Lyonnet
    Lyonnet is a French surname most notably associated with professional dancer Grégoire Lyonnet.
  • C. Roannais
    Roannais is a natural region in central France known for its rolling countryside, agricultural landscapes, and proximity to the upper Loire River.
  • D. Brionnais
    Brionnais is a historic rural region in eastern France known for its Romanesque churches, traditional stone villages, and Charolais cattle farming.
  • E. Auberjonois
    Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
  • 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a585795c8190aa8a5edf0d99b47f completed April 10, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f090d861f481909b920197a3d60e28 completed April 28, 2026, 10:50 a.m.
Created at: April 8, 2026, 9:42 p.m.