Triple

T17866079
Position Surface form Disambiguated ID Type / Status
Subject Camilla Horn E446706 entity
Predicate name P16 FINISHED
Object Camilla Horn 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: Camilla Horn | Statement: [Camilla Horn, name, Camilla Horn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Camilla Horn
Context triple: [Camilla Horn, name, Camilla Horn]
  • A. Camilla Horn chosen
    Camilla Horn was a German actress best known for her roles in silent and early sound films of the 1920s and 1930s, particularly in European cinema.
  • B. Sigrid Horne-Rasmussen
    Sigrid Horne-Rasmussen was a Danish actress known for her work in mid-20th-century Danish cinema and theatre.
  • C. Camilla Lund
    Camilla Lund is a Norwegian speed skater who has competed internationally as a member of Norway's national team.
  • D. Camilla Jessel
    Camilla Jessel is a British writer and the wife of Polish composer Andrzej Panufnik, known for her work documenting his life and legacy.
  • E. Camilla Rutherford
    Camilla Rutherford is a British actress and former model best known for her roles in period dramas such as "Gosford Park" and "Gosford Park."
  • 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_69d8b9f4c22c819093c2680434472894 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49793a2588190bb341ac606d767fe completed April 19, 2026, 8:51 a.m.
Created at: April 10, 2026, 10:17 a.m.