Triple

T14483682
Position Surface form Disambiguated ID Type / Status
Subject The Spy Who Came in from the Cold (1965 film) E359172 entity
Predicate musicBy P1952 FINISHED
Object Sol Kaplan E504336 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: Sol Kaplan | Statement: [The Spy Who Came in from the Cold (1965 film), musicBy, Sol Kaplan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sol Kaplan
Context triple: [The Spy Who Came in from the Cold (1965 film), musicBy, Sol Kaplan]
  • A. Sol Kaplan chosen
    Sol Kaplan was an American composer best known for his film and television scores, including work in mid-20th-century Hollywood.
  • B. Billy Kaplan
    Billy Kaplan is a Marvel Comics superhero, also known as Wiccan, who is a powerful magic user and a member of the Young Avengers.
  • C. Greg Kaplan
    Greg Kaplan is an economist known for his research on household heterogeneity, consumption, and macroeconomic policy, and for his contributions to modern macroeconomic modeling.
  • D. Hank Kaplan
    Hank Kaplan is a fictional character from the American medical drama television series "Nurses."
  • E. Larry Kaplan
    Larry Kaplan is a pioneering video game designer and programmer best known as one of the co-founders of Activision and an early developer for the Atari 2600.
  • 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_69d8279740308190af9df93a3af8592e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de924d7f4c8190b1f62b5ffe1ff649 completed April 14, 2026, 7:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a002d92c9788190aa4523a1e47bc561 completed May 10, 2026, 7:02 a.m.
Created at: April 10, 2026, 1:20 a.m.