Triple

T16801510
Position Surface form Disambiguated ID Type / Status
Subject l’Archange de la Terreur E408366 entity
Predicate countryOfContext P838 FINISHED
Object France E861 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: France | Statement: [l’Archange de la Terreur, countryOfContext, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: France
Context triple: [l’Archange de la Terreur, countryOfContext, France]
  • 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. 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.
  • E. de France
    "de France" is a dynastic surname historically used by members of the French royal family, particularly the legitimate children of reigning kings of France.
  • 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_69d88393905081908d00a86b99996ac8 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b2c826808190aa0a5bfcde2e49a8 completed April 18, 2026, 4:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00aaf3c6088190a8301a9613d74474 completed May 10, 2026, 3:57 p.m.
Created at: April 10, 2026, 5:22 a.m.