Triple

T13883566
Position Surface form Disambiguated ID Type / Status
Subject Marni Nixon E333777 entity
Predicate spouse P13 FINISHED
Object Ernest Gold E171743 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: Ernest Gold | Statement: [Marni Nixon, spouse, Ernest Gold]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ernest Gold
Context triple: [Marni Nixon, spouse, Ernest Gold]
  • A. Ernest Gold chosen
    Ernest Gold was an Austrian-born American composer best known for his acclaimed film scores, including the Oscar-winning music for "Exodus."
  • B. Bernard Newman
    Bernard Newman was an American costume designer best known for his glamorous work in 1930s Hollywood musicals and films.
  • C. Elmer Bernstein
    Elmer Bernstein was an American composer renowned for his prolific and influential film scores across genres, including classics like "The Ten Commandments," "The Magnificent Seven," and "To Kill a Mockingbird."
  • D. David Raksin
    David Raksin was an American film composer best known for his influential scores in classic Hollywood cinema, including the iconic music for the film "Laura."
  • E. Earle Hagen
    Earle Hagen was an American composer and arranger best known for his iconic television themes, including the whistled opening of The Andy Griffith Show.
  • 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_69d81c5dd2d48190b7a5fc1e009de936 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0bea4d248190bcbcea9ea875c5f9 completed April 14, 2026, 9:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69fbc31c38e481909a86cda6c913fb8e completed May 6, 2026, 10:39 p.m.
Created at: April 9, 2026, 10:15 p.m.