Triple

T20469122
Position Surface form Disambiguated ID Type / Status
Subject Peter Hyams E502136 entity
Predicate notableWork P4 FINISHED
Object Narrow Margin 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: Narrow Margin | Statement: [Peter Hyams, notableWork, Narrow Margin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Narrow Margin
Context triple: [Peter Hyams, notableWork, Narrow Margin]
  • A. Narrow Margin chosen
    Narrow Margin is a 1990 American thriller film starring Gene Hackman as a district attorney protecting a murder witness aboard a moving train.
  • B. The Narrow Margin
    The Narrow Margin is a 1952 American film noir thriller, celebrated for its taut, suspenseful story about a cop protecting a mobster’s widow on a perilous train journey.
  • C. The Narrow Margin
    The Narrow Margin is a highly regarded historical account of the Battle of Britain, detailing the air campaign’s strategy, combat, and significance in World War II.
  • D. Close Edge
    "Close Edge" is a track by rapper and actor Mos Def from his genre-blending 2004 album *The New Danger*.
  • E. Margin for Error
    "Margin for Error" is a 1939 satirical play by Clare Boothe Luce that blends comedy and political commentary around a murder mystery involving a Nazi consul in New York.
  • 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_69e0b4ae5f1081908768b0c9a3a0bf38 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6995f753081909bbe03f7c251d9c1 completed April 20, 2026, 9:23 p.m.
Created at: April 16, 2026, 11:33 a.m.