Triple

T10463275
Position Surface form Disambiguated ID Type / Status
Subject Get Carter E246728 entity
Predicate editedBy P1954 FINISHED
Object John Trumper E866167 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 Trumper | Statement: [Get Carter, editedBy, John Trumper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Trumper
Context triple: [Get Carter, editedBy, John Trumper]
  • A. John Trumper chosen
    John Trumper is a film editor best known for his work on notable movies such as "The Italian Job."
  • B. Fred Trumper
    Fred Trumper is the hapless, self-sabotaging graduate student and chronic liar at the center of John Irving’s comic novel "The Water-Method Man," known for his romantic misadventures and fear of commitment.
  • C. Johnny Worricker
    Johnny Worricker is a seasoned, quietly principled MI5 intelligence officer whose moral dilemmas drive the British political thriller film "Page Eight."
  • D. Johnny Brazier
    Johnny Brazier was an American stock car racer best known as a member of the famed Alabama Gang, a group of influential drivers in Southern short-track and NASCAR racing.
  • E. Johnny Mulhair
    Johnny Mulhair is a music producer best known for his work on country recordings such as LeAnn Rimes’ hit “One Way Ticket (Because I Can).”
  • 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_69d381c16c248190a2fe5b471e584e9c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d50885e220819089e455b646f31e65 completed April 7, 2026, 1:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dc4fbc3481909b214137f26e243b completed April 10, 2026, 11:17 a.m.
Created at: April 6, 2026, 12:19 p.m.