Triple

T22946848
Position Surface form Disambiguated ID Type / Status
Subject Wind E569896 entity
Predicate cinematographer P1953 FINISHED
Object John Toll 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: John Toll | Statement: [Wind, cinematographer, John Toll]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Toll
Context triple: [Wind, cinematographer, John Toll]
  • A. John Toll chosen
    John Toll is an acclaimed American cinematographer known for his visually striking work on numerous major films, including "The Adjustment Bureau."
  • B. Joe Johnston
    Joe Johnston is an American film director and visual effects artist best known for directing movies such as "Honey, I Shrunk the Kids," "Jumanji," and "Captain America: The First Avenger."
  • C. Roger Christian
    Roger Christian was an American ice hockey player from Warroad, Minnesota, best known for winning a gold medal with the U.S. national team at the 1960 Winter Olympics.
  • D. Roger Christian
    Roger Christian was an American lyricist and radio DJ best known for co-writing many of the Beach Boys’ early car-themed hits in the 1960s.
  • E. Eric Roth
    Eric Roth is an acclaimed American screenwriter best known for writing the Oscar-winning screenplay for "Forrest Gump" and contributing to numerous other major films.
  • 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_69e2459199d08190a8184ee2aa935842 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1819e559c81909e63acfc23f9476b completed April 29, 2026, 3:57 a.m.
Created at: April 17, 2026, 3:46 p.m.