Triple

T14500196
Position Surface form Disambiguated ID Type / Status
Subject Trevor Macy E359612 entity
Predicate employer P7 FINISHED
Object Intrepid Pictures E1086886 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: Intrepid Pictures | Statement: [Trevor Macy, employer, Intrepid Pictures]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Intrepid Pictures
Context triple: [Trevor Macy, employer, Intrepid Pictures]
  • A. Intrepid Pictures chosen
    Intrepid Pictures is an American film and television production company known for producing horror and thriller projects, including several Stephen King adaptations and collaborations with filmmaker Mike Flanagan.
  • B. Myriad Pictures
    Myriad Pictures is an independent film production and distribution company known for handling a range of arthouse and specialty films.
  • C. Troika Pictures
    Troika Pictures is a film production company known for producing feature films such as the thriller "The Call" (2013).
  • D. Prospero Pictures
    Prospero Pictures is a Canadian film production company known for backing independent and auteur-driven films, including works by director David Cronenberg.
  • E. Everest Pictures
    Everest Pictures is a film production company known for producing the psychological drama "David and Lisa."
  • 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_69d8279740308190af9df93a3af8592e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de94dfe484819086dd971606e6478e completed April 14, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a420040819097ee73390d625338 completed May 8, 2026, 5:53 a.m.
Created at: April 10, 2026, 1:21 a.m.