Triple

T18796239
Position Surface form Disambiguated ID Type / Status
Subject Notre-Dame de l’Arche d’Alliance E459640 entity
Predicate locatedIn P40 FINISHED
Object France, Europe NE NERFINISHED

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: France, Europe | Statement: [Notre-Dame de l’Arche d’Alliance, locatedIn, France, Europe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: France, Europe
Context triple: [Notre-Dame de l’Arche d’Alliance, locatedIn, France, Europe]
  • A. France chosen
    France is a major Western European nation known for its influential history, culture, and economy, and as a founding member of the European Union and the United Nations.
  • B. Lafrançaise, France
    Lafrançaise is a small commune in the Tarn-et-Garonne department of southern France, known for its rural charm and traditional French village atmosphere.
  • C. La France
    La France is a renowned sculpture by French artist Antoine Bourdelle that powerfully symbolizes the spirit and identity of France.
  • D. Francia
    Francia is the surname of American rower and two-time Olympic gold medalist Susan Francia.
  • E. mainland France
    Mainland France is the European continental part of the French Republic, encompassing its largest and most populous territory including major cities like Paris, Lyon, and Marseille.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d398c7d4819091cb2f7e48948aeb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5a01ed3c08190890d9518ed69fdee completed April 20, 2026, 3:40 a.m.
Created at: April 10, 2026, 11:53 a.m.