Triple

T4052142
Position Surface form Disambiguated ID Type / Status
Subject Inferno (film) E84608 entity
Predicate screenwriter P2831 FINISHED
Object David Koepp E70760 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: David Koepp | Statement: [Inferno (film), screenwriter, David Koepp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David Koepp
Context triple: [Inferno (film), screenwriter, David Koepp]
  • A. David Koepp chosen
    David Koepp is an American screenwriter and director best known for writing major Hollywood films such as Jurassic Park, Mission: Impossible, and Spider-Man.
  • B. Zak Penn
    Zak Penn is an American screenwriter and director known for his work on major science fiction and superhero films such as "The Avengers," "X2," and "Ready Player One."
  • C. Tony Gilroy
    Tony Gilroy is an American filmmaker and screenwriter best known for writing the Bourne film series and directing the acclaimed thriller "Michael Clayton."
  • D. Scott Z. Burns
    Scott Z. Burns is an American screenwriter, director, and producer known for socially conscious films such as Contagion, The Informant!, and The Report.
  • E. Steve Kloves
    Steve Kloves is an American screenwriter best known for adapting most of the Harry Potter novels into the successful film 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_69aed933bec881909edfa28ebb69c634 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb869c34819097ec3bebe402d37b completed March 9, 2026, 4:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69b56b501c008190ac115240328c6fc9 completed March 14, 2026, 2:06 p.m.
Created at: March 9, 2026, 3:37 p.m.