Triple

T6904481
Position Surface form Disambiguated ID Type / Status
Subject Joel McCrea E159573 entity
Predicate name P16 FINISHED
Object Joel McCrea E159573 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: Joel McCrea | Statement: [Joel McCrea, name, Joel McCrea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joel McCrea
Context triple: [Joel McCrea, name, Joel McCrea]
  • A. Joel McCrea chosen
    Joel McCrea was an American film actor best known for his leading roles in classic Hollywood Westerns and comedies from the 1930s through the 1950s.
  • B. Randolph Scott
    Randolph Scott was a prominent American film actor best known for his roles in Westerns during the 1930s–1950s.
  • C. Robert Cummings
    Robert Cummings was an American film and television actor best known for his roles in comedies and thrillers during Hollywood’s Golden Age.
  • D. Zachary Scott
    Zachary Scott was an American actor best known for his suave yet often villainous roles in 1940s and 1950s Hollywood films.
  • E. William McMurray
    William McMurray was a historical figure after whom the Canadian city of Fort McMurray in Alberta was named, likely due to his role in the region’s early development or exploration.
  • 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_69c6883822e0819091e321526f20ae0a completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6d989c13081908a2e346cde9e3a50 completed March 27, 2026, 7:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c748f6640481908b74903a47e1eb18 completed March 28, 2026, 3:20 a.m.
Created at: March 27, 2026, 2:25 p.m.