Triple

T9117084
Position Surface form Disambiguated ID Type / Status
Subject Leon Shamroy E218746 entity
Predicate workedOn P3 FINISHED
Object Leave Her to Heaven E395660 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: Leave Her to Heaven | Statement: [Leon Shamroy, workedOn, Leave Her to Heaven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leave Her to Heaven
Context triple: [Leon Shamroy, workedOn, Leave Her to Heaven]
  • A. Leave Her to Heaven chosen
    Leave Her to Heaven is a 1945 Technicolor film noir melodrama starring Gene Tierney, renowned for its lush visuals and psychologically intense story of obsessive love.
  • B. For Heaven's Sake
    For Heaven's Sake is a 1926 silent romantic comedy film starring Harold Lloyd as a wealthy man who becomes involved with a mission worker in the city's slums.
  • C. No Place in Heaven
    No Place in Heaven is a 2015 pop album by British-Lebanese singer-songwriter Mika that blends theatrical melodies with introspective, personal lyrics.
  • D. Heaven Knows
    "Heaven Knows" is a song featured on Lenny Kravitz's album *Blue Electric Light*.
  • E. Lady of Heaven
    Lady of Heaven is an epithet of the ancient Egyptian goddess Mut, highlighting her role as a powerful celestial mother and queen among the gods.
  • 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_69ca83dc94ac8190b9ef42684d36ff39 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cca8a4c9e08190ba3603a5d00afb20 completed April 1, 2026, 5:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d047baf5e48190aab0eb19908fabfc completed April 3, 2026, 11:05 p.m.
Created at: March 30, 2026, 7:17 p.m.