Triple

T22127115
Position Surface form Disambiguated ID Type / Status
Subject Four E546816 entity
Predicate producer P490 FINISHED
Object Jake Gosling NE NERFINISHED

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: Jake Gosling | Statement: [Four, producer, Jake Gosling]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jake Gosling
Context triple: [Four, producer, Jake Gosling]
  • A. Jake Gosling chosen
    Jake Gosling is a British music producer and songwriter best known for his work with artists like Ed Sheeran and One Direction.
  • B. Ryan Gosling
    Ryan Gosling is a Canadian actor known for his versatile performances in films ranging from romantic dramas like "The Notebook" to critically acclaimed works such as "La La Land" and "Drive."
  • C. Leon Allen Goslin
    Leon Allen "Goose" Goslin was a Hall of Fame American Major League Baseball left fielder known for his powerful hitting during the 1920s and 1930s.
  • D. Josh Hartnett
    Josh Hartnett is an American actor known for his breakout roles in late-1990s and early-2000s films such as "The Faculty," "Pearl Harbor," and "Black Hawk Down," as well as later work in projects like the series "Penny Dreadful."
  • E. Justin Long
    Justin Long is an American actor known for his comedic and romantic comedy roles in films like "Dodgeball," "Accepted," and the "I'm a Mac" Apple commercials.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e39bf348190b541bfa16a7b71e0 completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f12982eaa08190933d3036c020f562 completed April 28, 2026, 9:41 p.m.
Created at: April 16, 2026, 8:31 p.m.