Triple

T4356052
Position Surface form Disambiguated ID Type / Status
Subject Die Hard E98150 entity
Predicate director P255 FINISHED
Object John McTiernan E151463 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 McTiernan | Statement: [Die Hard, director, John McTiernan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John McTiernan
Context triple: [Die Hard, director, John McTiernan]
  • A. John McTiernan chosen
    John McTiernan is an American film director best known for influential action movies such as "Die Hard" and "Predator."
  • B. David Friedkin
    David Friedkin was an American screenwriter, director, and producer known for his work in mid-20th-century film and television.
  • C. John Boyd-Carpenter
    John Boyd-Carpenter was a British Conservative politician and government minister who held several senior posts in the mid-20th century, including key roles in economic and social policy.
  • D. Michael Cimino
    Michael Cimino was an American film director and screenwriter best known for his ambitious, visually striking dramas and his Oscar-winning work on the Vietnam War epic "The Deer Hunter."
  • E. John Carpenter
    John Carpenter is an American filmmaker and composer best known for directing influential horror and science fiction films such as "Halloween," "The Thing," and "Escape from New York."
  • 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_69b3454965f881908c41190bb22f0e4b completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b351c5773481908446d84897e7a533 completed March 12, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5e501671c8190bf8a9998f46a9f3b completed March 14, 2026, 10:45 p.m.
Created at: March 12, 2026, 11:16 p.m.