Triple

T22016938
Position Surface form Disambiguated ID Type / Status
Subject Berkeley Repertory Theatre E543736 entity
Predicate founder P104 FINISHED
Object Michael Leibert 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 Leibert | Statement: [Berkeley Repertory Theatre, founder, Michael Leibert]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Leibert
Context triple: [Berkeley Repertory Theatre, founder, Michael Leibert]
  • A. Michael Leibert chosen
    Michael Leibert was an American theater director and producer best known for establishing the influential Berkeley Repertory Theatre in California.
  • B. Ken Lemberger
    Ken Lemberger is a film producer known for his work on the 2006 adaptation of "All the King's Men."
  • C. Michael Lucker
    Michael Lucker is an American screenwriter known for his work on animated and family films, including contributions to Disney projects.
  • D. Ken Lauber
    Ken Lauber is an American composer and musician known for his film and television scores, blending elements of jazz, classical, and popular music.
  • E. Michael Leiters
    Michael Leiters is an automotive executive known for senior leadership roles at high-performance sports car manufacturers, including serving as CEO of McLaren Automotive.
  • 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_69e11e2e8ea4819084210fe06d3a1b8d completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f127a8a1388190b9e0c1795fe1183a completed April 28, 2026, 9:33 p.m.
Created at: April 16, 2026, 8:23 p.m.