Triple

T8028799
Position Surface form Disambiguated ID Type / Status
Subject Carousel (film) E186922 entity
Predicate stars P1956 FINISHED
Object Gordon MacRae E48300 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: Gordon MacRae | Statement: [Carousel (film), stars, Gordon MacRae]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gordon MacRae
Context triple: [Carousel (film), stars, Gordon MacRae]
  • A. Gordon MacRae chosen
    Gordon MacRae was an American actor and singer best known for his leading roles in classic Hollywood film musicals such as "Oklahoma!" and "Carousel."
  • B. Bob Merrill
    Bob Merrill was an American songwriter and lyricist best known for his work on Broadway musicals and popular songs in the mid-20th century.
  • C. Howard Keel
    Howard Keel was an American actor and baritone singer best known for his leading roles in classic MGM musicals of the 1950s and later for his role on the TV series "Dallas."
  • D. Cliff Hayes
    Cliff Hayes is a film editor best known for his work on the influential Australian action film "Mad Max."
  • E. Perry Como
    Perry Como was an American singer and television personality renowned for his smooth baritone voice, relaxed crooning style, and decades-long presence as a popular music and TV star in the mid-20th century.
  • 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_69ca82ad4e2c8190a693e3c9e30fe66f completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3ecdbc5881909246982b93978841 completed March 31, 2026, 3:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc56e146048190a97b3b37d1eec0b8 completed March 31, 2026, 11:21 p.m.
Created at: March 30, 2026, 5:21 p.m.