Triple

T2022366
Position Surface form Disambiguated ID Type / Status
Subject Jurassic World E44132 entity
Predicate cinematographyBy P1953 FINISHED
Object John Schwartzman E138073 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: John Schwartzman | Statement: [Jurassic World, cinematographyBy, John Schwartzman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Schwartzman
Context triple: [Jurassic World, cinematographyBy, John Schwartzman]
  • A. John Schwartzman chosen
    John Schwartzman is an American cinematographer known for his work on major Hollywood films, including action blockbusters and large-scale studio productions.
  • B. Michael Schaefer
    Michael Schaefer is a film and television producer known for his executive production work on projects such as the series "Swarm."
  • C. Marc Streitenfeld
    Marc Streitenfeld is a German film score composer best known for his frequent collaborations with director Ridley Scott on major Hollywood films.
  • D. Daniel Tarschys
    Daniel Tarschys is a Swedish political scientist and politician who served as Secretary General of the Council of Europe in the 1990s.
  • E. Jonathan Teplitzky
    Jonathan Teplitzky is an Australian film director known for character-driven dramas such as "The Railway Man" and "Burning Man."
  • 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_69a8891201bc8190aca837be6de41579 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb8efbe148190901d3650aa60408a completed March 7, 2026, 5:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fe88e8881909f2e64ebe23b6d1f completed March 9, 2026, 1:18 a.m.
Created at: March 4, 2026, 7:38 p.m.