Triple

T12657413
Position Surface form Disambiguated ID Type / Status
Subject Inferno (1980 film) E302320 entity
Predicate screenwriter P2831 FINISHED
Object Michael Kane E357839 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: Michael Kane | Statement: [Inferno (1980 film), screenwriter, Michael Kane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Kane
Context triple: [Inferno (1980 film), screenwriter, Michael Kane]
  • A. Michael Kane chosen
    Michael Kane is a screenwriter best known for writing the 1983 American sports drama film "All the Right Moves."
  • B. Michael Jace
    Michael Jace is an American actor best known for his role as LAPD Officer Julien Lowe on the television series "The Shield."
  • C. Vic Morrow
    Vic Morrow was an American actor best known for his role in the television series "Combat!" and for his tragic death in a helicopter accident during the filming of "Twilight Zone: The Movie."
  • D. Seymour Cassel
    Seymour Cassel was an American character actor known for his longtime collaboration with director John Cassavetes and his roles in numerous independent and mainstream films.
  • E. Robert Parrish
    Robert Parrish was an American film editor and director, as well as a former child actor, known for his work on several classic Hollywood films.
  • 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_69d7bded71a88190bb76e2413af9ea66 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961636db8819099c438b24bcfd866 completed April 10, 2026, 8:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68ead66bc819099c8d274d69a2022 completed May 2, 2026, 11:54 p.m.
Created at: April 9, 2026, 5:18 p.m.