Triple

T7775593
Position Surface form Disambiguated ID Type / Status
Subject The Big Heat E221381 entity
Predicate starring P1507 FINISHED
Object Gloria Grahame E56481 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: Gloria Grahame | Statement: [The Big Heat, starring, Gloria Grahame]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gloria Grahame
Context triple: [The Big Heat, starring, Gloria Grahame]
  • A. Gloria Grahame chosen
    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.
  • B. Ava Gardner
    Ava Gardner was a celebrated American film actress and Hollywood icon of the 1940s and 1950s, renowned for her beauty, charisma, and roles in classics such as "The Killers" and "Mogambo."
  • C. Lizabeth Scott
    Lizabeth Scott was an American film actress known for her sultry voice and frequent roles as a femme fatale in 1940s and 1950s film noir.
  • D. Lana Turner
    Lana Turner was a glamorous American film actress and iconic Hollywood star of the 1940s and 1950s, renowned for her dramatic roles and enduring screen presence.
  • E. Linda Darnell
    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."
  • 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_69ca83ebbef881909ac47f789145fef7 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69caa4d005808190ac14c8d716421bdb completed March 30, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69caf58a86548190b870417692e4b654 completed March 30, 2026, 10:13 p.m.
Created at: March 30, 2026, 3:46 p.m.