Triple

T18099699
Position Surface form Disambiguated ID Type / Status
Subject Nakatomi Plaza E433181 entity
Predicate associatedWithCharacter P1481 FINISHED
Object John McClane — 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: John McClane | Statement: [Nakatomi Plaza, associatedWithCharacter, John McClane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John McClane
Context triple: [Nakatomi Plaza, associatedWithCharacter, John McClane]
  • A. John McClane chosen
    John McClane is the tough, wisecracking New York cop and everyman action hero famously portrayed by Bruce Willis in the Die Hard film series.
  • B. John McClain
    John McClain was a screenwriter active in classic Hollywood cinema, known for his work on mid-20th-century American films.
  • C. John McClain
    John McClain is a music industry executive and record producer best known as a co-founder of Interscope Records and for managing and working with major artists.
  • D. Karl in Die Hard
    Karl in Die Hard is a ruthless, long-haired German terrorist and henchman who serves as one of John McClane’s primary adversaries in the 1988 action film.
  • E. John Shaft
    John Shaft is a tough, streetwise New York City detective and iconic blaxploitation hero known for his cool demeanor and relentless pursuit of justice.
  • 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_69d8b90916008190a1f110bd7ced5473 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4ddb521448190b97d2b2aa7e4d7e6 completed April 19, 2026, 1:50 p.m.
Created at: April 10, 2026, 10:27 a.m.