Triple

T18555523
Position Surface form Disambiguated ID Type / Status
Subject Arausio E453492 entity
Predicate country P26 FINISHED
Object France (modern location) 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 (modern location) | Statement: [Arausio, country, France (modern location)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: France (modern location)
Context triple: [Arausio, country, France (modern location)]
  • 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. La France
    La France is a renowned sculpture by French artist Antoine Bourdelle that powerfully symbolizes the spirit and identity of France.
  • C. Francia
    Francia is the surname of American rower and two-time Olympic gold medalist Susan Francia.
  • D. 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.
  • E. 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.
  • 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_69d8d388b0c881908e610a1c45b52640 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e53806046481908efbbe6909b2c68b completed April 19, 2026, 8:16 p.m.
Created at: April 10, 2026, 11:38 a.m.