Triple

T10360097
Position Surface form Disambiguated ID Type / Status
Subject Naser al-Din Shah Qajar E244109 entity
Predicate visited P2694 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: [Naser al-Din Shah Qajar, visited, France]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: France
Context triple: [Naser al-Din Shah Qajar, visited, 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. Francia
    Francia is the surname of American rower and two-time Olympic gold medalist Susan Francia.
  • C. État français
    État français was the authoritarian regime led by Marshal Philippe Pétain that governed unoccupied France from Vichy during World War II and collaborated with Nazi Germany.
  • D. 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.
  • E. France Ô
    France Ô was a French public television channel dedicated to programming from France’s overseas departments and territories, operated by the France Télévisions group.
  • 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_69d381b22b8c8190aaed476be5f872a9 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9609c4481908b7d72ecf1adaa73 completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d74fe436d48190b889ccf5884d1bb7 completed April 9, 2026, 7:06 a.m.
Created at: April 6, 2026, 11:59 a.m.