Triple

T10682141
Position Surface form Disambiguated ID Type / Status
Subject RoboCop E251783 entity
Predicate director P255 FINISHED
Object Paul Verhoeven E329582 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: Paul Verhoeven | Statement: [RoboCop, director, Paul Verhoeven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Verhoeven
Context triple: [RoboCop, director, Paul Verhoeven]
  • A. Paul Verhoeven chosen
    Paul Verhoeven is a Dutch filmmaker known for his provocative, violent, and satirical films such as RoboCop, Total Recall, and Starship Troopers.
  • B. Bob Noorda
    Bob Noorda was a renowned Dutch graphic designer celebrated for his pioneering work in modernist corporate and transportation visual identity systems.
  • C. Fred Dekker
    Fred Dekker is an American filmmaker and screenwriter best known for cult horror and sci-fi films such as "Night of the Creeps," "The Monster Squad," and his collaborations with Shane Black.
  • D. Jan de Bont
    Jan de Bont is a Dutch cinematographer and film director best known for shooting visually dynamic action films and directing hits like Speed and Twister.
  • E. David Friedkin
    David Friedkin was an American screenwriter, director, and producer known for his work in mid-20th-century film and television.
  • 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_69d6aa5bd7c08190a816e733b4045c23 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fcc30be481909922844b539b622d completed April 9, 2026, 1:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d98885abf88190b54ed9db779d3ff0 completed April 10, 2026, 11:32 p.m.
Created at: April 8, 2026, 9:10 p.m.