Triple

T6333171
Position Surface form Disambiguated ID Type / Status
Subject Magic in the Moonlight E142428 entity
Predicate producer P490 FINISHED
Object Letty Aronson E312157 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: Letty Aronson | Statement: [Magic in the Moonlight, producer, Letty Aronson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Letty Aronson
Context triple: [Magic in the Moonlight, producer, Letty Aronson]
  • A. Letty Aronson chosen
    Letty Aronson is an American film producer best known for her long-running collaboration with director Woody Allen on numerous critically acclaimed movies.
  • B. Letty Ortiz
    Letty Ortiz is a skilled street racer, mechanic, and key member of Dominic Toretto’s crew in the Fast & Furious film franchise.
  • C. Joan Valentine
    Joan Valentine is a quick-witted, resourceful young woman who works as a journalist and adventurer in P. G. Wodehouse’s comic fiction.
  • D. Aileen Marlowe
    Aileen Marlowe was the wife of American film and television actor Hugh Marlowe.
  • E. Laura Montez
    Laura Montez is a charismatic and politically ambitious U.S. politician in the TV series "Veep," who emerges as a major competitor and foil to Selina Meyer.
  • 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_69c008d4d8e88190ad301c05b08722ac completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c06517a1e88190a0bfcac8a7e3a305 completed March 22, 2026, 9:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c60424a5dc8190820970fce13776ac completed March 27, 2026, 4:14 a.m.
Created at: March 22, 2026, 4:30 p.m.