Triple

T20789980
Position Surface form Disambiguated ID Type / Status
Subject Europe/Vienna E511746 entity
Predicate countryCovered P98679 FINISHED
Object France (mainland) 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 (mainland) | Statement: [Europe/Vienna, countryCovered, France (mainland)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: France (mainland)
Context triple: [Europe/Vienna, countryCovered, France (mainland)]
  • A. France
    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 chosen
    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. Pays Royannais
    Pays Royannais is a coastal area in southwestern France centered around the town of Royan, known for its seaside resorts and Atlantic beaches.
  • 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_69e0b4cb83948190bd57bec21d78ed53 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c28f0e1081909f18dddfc6ec084c completed April 21, 2026, 12:19 a.m.
Created at: April 16, 2026, 12:38 p.m.