Triple

T22547313
Position Surface form Disambiguated ID Type / Status
Subject Sam Fisher E557460 entity
Predicate voiceActor P1507 FINISHED
Object Michael Ironside NE NERFINISHED

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 Ironside | Statement: [Sam Fisher, voiceActor, Michael Ironside]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Ironside
Context triple: [Sam Fisher, voiceActor, Michael Ironside]
  • A. Michael Ironside chosen
    Michael Ironside is a Canadian actor known for his intense, often villainous roles in science fiction and action films such as "Total Recall," "Starship Troopers," and "Top Gun."
  • B. John Doman
    John Doman is an American character actor known for his authoritative roles in television series such as "The Wire" and "Gotham" as well as numerous film appearances.
  • C. Michael Lonsdale
    Michael Lonsdale was a distinguished French-English actor known for his versatile performances in European cinema and Hollywood films, including roles in "The Day of the Jackal" and the James Bond film "Moonraker."
  • D. Michael Kane
    Michael Kane is a screenwriter best known for writing the 1983 American sports drama film "All the Right Moves."
  • E. Michael Kane
    Michael Kane is a creator known for developing the character Stefen Djordjevic.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e58662081909ae346ab384514ca completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15f366f208190abbc6eb4780b2d48 completed April 29, 2026, 1:30 a.m.
Created at: April 16, 2026, 8:52 p.m.