Triple

T11689306
Position Surface form Disambiguated ID Type / Status
Subject Lance Henriksen E277826 entity
Predicate notableWork P4 FINISHED
Object Hard Target E379697 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: Hard Target | Statement: [Lance Henriksen, notableWork, Hard Target]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hard Target
Context triple: [Lance Henriksen, notableWork, Hard Target]
  • A. Hard Target chosen
    Hard Target is a 1993 American action film directed by John Woo and starring Jean-Claude Van Damme, known for its stylized violence and Woo’s Hollywood debut.
  • B. Red Heat
    Red Heat is a 1988 buddy-cop action film starring Arnold Schwarzenegger and James Belushi, directed by Walter Hill.
  • C. Savage Streets
    Savage Streets is a 1984 exploitation revenge thriller film starring Linda Blair as a high-school vigilante avenging a brutal attack on her sister.
  • D. Point Blank
    Point Blank is a segment or component of the larger work titled "The River," likely representing a distinct chapter, track, or section within that overall composition.
  • E. Point Blank
    Point Blank is a 1967 neo-noir crime film starring Lee Marvin, noted for its stylish direction and influential, hard-edged portrayal of revenge.
  • 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_69d6aafe02d881909900d54ad7d4af84 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a478f4c481908b2ba7b70972590d completed April 10, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef1451b4708190be9aa0439aface7a completed April 27, 2026, 7:46 a.m.
Created at: April 8, 2026, 9:40 p.m.