Triple

T5050428
Position Surface form Disambiguated ID Type / Status
Subject Arpitania E113770 entity
Predicate overlapsWith P1867 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: [Arpitania, overlapsWith, Lyonnais]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lyonnais
Context triple: [Arpitania, overlapsWith, 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. Brionnais
    Brionnais is a historic rural region in eastern France known for its Romanesque churches, traditional stone villages, and Charolais cattle farming.
  • C. Auberjonois
    Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
  • D. Tournefeuillais
    Tournefeuillais is the French demonym for inhabitants of the commune of Tournefeuille in southwestern France.
  • E. Libournais
    Libournais is a renowned wine-producing region on Bordeaux’s Right Bank in southwestern France, known for its Merlot-dominant red wines and appellations such as Pomerol and Saint-Émilion.
  • 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_69bd44391fc48190a311ce9c826c209b completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7425df74819091cfde348dd16a68 completed March 20, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea480fee88190a4302301259f29ba completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:37 p.m.