Triple

T661055
Position Surface form Disambiguated ID Type / Status
Subject Hell on Wheels E11755 entity
Predicate executiveProducer P7225 FINISHED
Object Joe Gayton E187164 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: Joe Gayton | Statement: [Hell on Wheels, executiveProducer, Joe Gayton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joe Gayton
Context triple: [Hell on Wheels, executiveProducer, Joe Gayton]
  • A. Joe Gayton chosen
    Joe Gayton is an American screenwriter and producer best known for co-creating the Western television drama series "Hell on Wheels."
  • B. Kevin Chapman
    Kevin Chapman is an American actor known for his tough, blue-collar character roles in film and television, including prominent parts in series like "Person of Interest" and "City on a Hill."
  • C. Tony Gayton
    Tony Gayton is an American screenwriter and producer best known for co-creating the Western television drama series "Hell on Wheels."
  • D. Lee Garmes
    Lee Garmes was an American cinematographer renowned for his innovative lighting and camera techniques in early Hollywood cinema, including his Academy Award-winning work on "Shanghai Express."
  • E. Charlie Smith
    Charlie Smith is a fictional protagonist featured as the central character in a narrative work.
  • 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_69a4932862a0819098be659c814e4981 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49fa954988190841740a587ace466 completed March 1, 2026, 8:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad8a8f35d48190a18cf924bf5f9e45 completed March 8, 2026, 2:41 p.m.
Created at: March 1, 2026, 7:36 p.m.