Triple

T5042606
Position Surface form Disambiguated ID Type / Status
Subject Zero Hour! E113579 entity
Predicate mainCastMember P5563 FINISHED
Object Linda Darnell E244618 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: Linda Darnell | Statement: [Zero Hour!, mainCastMember, Linda Darnell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Linda Darnell
Context triple: [Zero Hour!, mainCastMember, Linda Darnell]
  • A. Linda Darnell chosen
    Linda Darnell was an American film actress of the 1940s and 1950s, known for her beauty and roles in Hollywood classics such as "Forever Amber" and "A Letter to Three Wives."
  • B. Gloria Grahame
    Gloria Grahame was an American film actress known for her sultry screen presence and acclaimed roles in classic Hollywood films noir and dramas of the 1940s and 1950s.
  • C. Ruth Roman
    Ruth Roman was an American film and television actress best known for her leading role in Alfred Hitchcock’s thriller "Strangers on a Train" (1951).
  • D. Sylvia Sidney
    Sylvia Sidney was an American actress known for her work in 1930s crime dramas and later roles in films like "Beetlejuice" and "Mars Attacks!".
  • E. Anne Baxter
    Anne Baxter was an American actress known for her Academy Award–winning and nominated performances in classic films such as "The Razor's Edge," "All About Eve," and "The Ten Commandments."
  • 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_69bf219bdd208190990db4b0fa89066a completed March 21, 2026, 10:54 p.m.
Created at: March 20, 2026, 1:37 p.m.