Triple

T7499403
Position Surface form Disambiguated ID Type / Status
Subject Die Hard with a Vengeance E177219 entity
Predicate castMember P1668 FINISHED
Object Jeremy Irons E181880 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: Jeremy Irons | Statement: [Die Hard with a Vengeance, castMember, Jeremy Irons]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeremy Irons
Context triple: [Die Hard with a Vengeance, castMember, Jeremy Irons]
  • A. Jeremy Irons chosen
    Jeremy Irons is an acclaimed English actor known for his distinctive voice and versatile performances in film, television, and theatre.
  • B. John Hurt
    John Hurt was an acclaimed English actor known for his distinctive voice and powerful performances in films such as "The Elephant Man," "Alien," and "Midnight Express."
  • C. Michael York
    Michael York is an English actor known for his roles in films such as "Cabaret," "Logan's Run," and the "Austin Powers" series.
  • D. Joseph Fiennes
    Joseph Fiennes is an English actor known for his roles in films such as "Shakespeare in Love" and various historical and dramatic productions in both cinema and television.
  • E. Brian Michael Cox
    Brian Michael Cox is a Grammy-winning American songwriter and record producer known for his work on numerous R&B and pop hits.
  • 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_69c69f2696688190915a8458f2398211 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f598dfac8190a123daaac0784aee completed March 27, 2026, 9:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83c900ad081908506a2097f7fd30b completed March 28, 2026, 8:39 p.m.
Created at: March 27, 2026, 3:44 p.m.