Triple

T11464985
Position Surface form Disambiguated ID Type / Status
Subject The Wedding Night E271756 entity
Predicate starring P1507 FINISHED
Object Gary Cooper E62558 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: Gary Cooper | Statement: [The Wedding Night, starring, Gary Cooper]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gary Cooper
Context triple: [The Wedding Night, starring, Gary Cooper]
  • A. Gary Cooper chosen
    Gary Cooper was an iconic American film actor renowned for his understated, stoic performances in classic Hollywood films, including major roles in Westerns and dramas.
  • B. Clark Gable
    Clark Gable was a legendary American film actor, best known for his charismatic leading roles in classic Hollywood films such as "Gone with the Wind."
  • C. John Clark Gable
    John Clark Gable is an American former racing driver and the only son of legendary Hollywood actor Clark Gable.
  • D. Glenn Ford
    Glenn Ford was a Canadian-American film actor renowned for his versatile performances in classic Hollywood movies such as "Gilda," "The Big Heat," and "Blackboard Jungle."
  • E. Melvyn Douglas
    Melvyn Douglas was an acclaimed American actor known for his sophisticated screen presence and award-winning performances in both classic Hollywood films and later character roles.
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d822f5eb988190b309b8e309f6d1a5 completed April 9, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69e6248d0db881909999049356f53ff6 completed April 20, 2026, 1:05 p.m.
Created at: April 8, 2026, 9:35 p.m.