Triple

T2462003
Position Surface form Disambiguated ID Type / Status
Subject Schindler's List E54552 entity
Predicate editor 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: [Schindler's List, editor, Michael Kahn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Kahn
Context triple: [Schindler's List, editor, 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. Marty Katz
    Marty Katz is a film producer known for his work on movies such as the World War II drama "The Great Raid."
  • C. Andrew Weisblum
    Andrew Weisblum is an American film editor known for his work on major feature films, including collaborations with directors like Darren Aronofsky and Wes Anderson.
  • D. Hal Bidlack
    Hal Bidlack is an American political science professor, retired U.S. Air Force officer, and public speaker known for his work in skepticism and secular humanism.
  • E. Sam Jaffe
    Sam Jaffe was an American actor and character performer known for memorable roles in classic films such as "Gunga Din," "The Asphalt Jungle," and "Ben-Hur."
  • 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_69ab49dee84c819096b50a0049c347ac completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd11f093c8190877db3026d430bd5 completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69b03104c21c81909fede29ce1e76d88 completed March 10, 2026, 2:56 p.m.
Created at: March 6, 2026, 9:44 p.m.