Triple

T17331981
Position Surface form Disambiguated ID Type / Status
Subject Death Wish E420837 entity
Predicate character P662 FINISHED
Object Paul Kersey E882175 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 Kersey | Statement: [Death Wish, character, Paul Kersey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Kersey
Context triple: [Death Wish, character, Paul Kersey]
  • A. Paul Kersey chosen
    Paul Kersey is the vigilante protagonist of the "Death Wish" film series, known for taking the law into his own hands after personal tragedy.
  • B. Bo Decker
    Bo Decker is the brash, naive young cowboy who serves as the central romantic figure in William Inge’s play "Bus Stop."
  • C. Art Donovan
    Art Donovan was a Hall of Fame defensive tackle for the Baltimore Colts, renowned for his dominant play in the 1950s and his colorful, larger-than-life personality.
  • D. Kevin Dunne
    Kevin Dunne is a central character in the film "Snake Eyes," portrayed as a high-ranking military officer whose actions drive the movie’s conspiracy-laden plot.
  • E. Jeffrey Caine
    Jeffrey Caine is a British screenwriter best known for co-writing the James Bond film "GoldenEye" and earning an Academy Award nomination for his adaptation of "The Constant Gardener."
  • 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_69d889d3adc881909319f1edb8d2a956 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e439d6870c8190989897aa6beba8ff completed April 19, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a018c5025d08190ab2581a3b04ae661 completed May 11, 2026, 7:59 a.m.
Created at: April 10, 2026, 5:43 a.m.