Triple

T23101421
Position Surface form Disambiguated ID Type / Status
Subject The Big Steal (1990 film) E576039 entity
Predicate mainCharacter P1183 FINISHED
Object Danny Clark 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: Danny Clark | Statement: [The Big Steal (1990 film), mainCharacter, Danny Clark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danny Clark
Context triple: [The Big Steal (1990 film), mainCharacter, Danny Clark]
  • A. Danny Clark chosen
    Danny Clark is the protagonist of the 2010 Australian crime-comedy film "The Big Steal," around whom the story’s central heist and ensuing misadventures revolve.
  • B. Les Clark
    Les Clark was an American animator and one of Disney’s famed "Nine Old Men," known for his influential work on many classic Disney films.
  • C. Dan McCarroll
    Dan McCarroll is an American music executive, producer, and former drummer known for his leadership roles at major record labels such as Capitol Records and Warner Bros. Records.
  • D. Donnie Clark
    Donnie Clark is a musician best known as a member of the country rock band Pure Prairie League.
  • E. Dane Clark
    Dane Clark was an American film and television actor known for his tough, working-class persona in numerous 1940s and 1950s Hollywood dramas and war movies.
  • 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_69e245c060b48190a9bd61a47a16db17 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f18de8c5b4819095cddf989cade60d completed April 29, 2026, 4:49 a.m.
Created at: April 17, 2026, 3:58 p.m.