Triple

T3785012
Position Surface form Disambiguated ID Type / Status
Subject Casper (1995 film) E85509 entity
Predicate editedBy P1954 FINISHED
Object Michael Kahn E255464 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 Kahn | Statement: [Casper (1995 film), editedBy, Michael Kahn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Kahn
Context triple: [Casper (1995 film), editedBy, Michael Kahn]
  • A. Michael Kahn chosen
    Michael Kahn is an acclaimed American film editor best known for his long-time collaboration with director Steven Spielberg on numerous major films.
  • B. Mitch Kertzman
    Mitch Kertzman is an American technology executive and entrepreneur best known for his leadership roles in the software and semiconductor industries, including at companies like LSI Logic and Sybase.
  • C. Ian Kahn
    Ian Kahn is an American actor best known for playing George Washington on the television series "Turn: Washington's Spies."
  • D. Michael Vavitch
    Michael Vavitch was a silent-era film actor known for his role in the 1924 drama "The Red Lily."
  • E. Marty Katz
    Marty Katz is a film producer known for his work on movies such as the World War II drama "The Great Raid."
  • 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_69aed937fa8881908208ef3801060826 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee3dd80f08190a1704521a764e22c completed March 9, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69bec330d09c819085930d71b21acb7c completed March 21, 2026, 4:11 p.m.
Created at: March 9, 2026, 3:13 p.m.