Triple

T5042605
Position Surface form Disambiguated ID Type / Status
Subject Zero Hour! E113579 entity
Predicate mainCastMember P5563 FINISHED
Object Dana Andrews E391255 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: Dana Andrews | Statement: [Zero Hour!, mainCastMember, Dana Andrews]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dana Andrews
Context triple: [Zero Hour!, mainCastMember, Dana Andrews]
  • A. Dana Andrews chosen
    Dana Andrews was a prominent American film actor of the 1940s and 1950s, best known for his leading roles in classics such as "Laura" and "The Best Years of Our Lives."
  • B. 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.
  • C. Farley Granger
    Farley Granger was an American actor best known for his roles in classic mid-20th-century films such as Alfred Hitchcock’s "Rope" and "Strangers on a Train."
  • D. William Holden
    William Holden was an acclaimed American film actor known for his charismatic performances in classics such as "Sunset Boulevard," "Stalag 17," and "The Bridge on the River Kwai."
  • E. 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."
  • 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_69bd44391fc48190a311ce9c826c209b completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73df8f7481909a8b86c4ae69aab9 completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfb70320ac819088ba3b1da868d9a4 completed March 22, 2026, 9:31 a.m.
Created at: March 20, 2026, 1:37 p.m.