Triple

T11171412
Position Surface form Disambiguated ID Type / Status
Subject Hans Gruber E264280 entity
Predicate killedBy P4646 FINISHED
Object John McClane E433178 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: John McClane | Statement: [Hans Gruber, killedBy, John McClane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John McClane
Context triple: [Hans Gruber, killedBy, 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. 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.
  • E. Johnny Cage
    Johnny Cage is a cocky Hollywood action movie star and skilled martial artist known for his flashy moves and comic relief role in the Mortal Kombat fighting game series.
  • 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e89660208190b1d9e91529f5d246 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e483816af08190877f86ee52846581 completed April 19, 2026, 7:25 a.m.
Created at: April 8, 2026, 9:29 p.m.