Triple

T9789807
Position Surface form Disambiguated ID Type / Status
Subject End of Watch E237578 entity
Predicate producer P490 FINISHED
Object John Lesher E285424 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: John Lesher | Statement: [End of Watch, producer, John Lesher]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Lesher
Context triple: [End of Watch, producer, John Lesher]
  • A. John Lesher chosen
    John Lesher is an American film producer best known for his work on acclaimed, auteur-driven movies such as the Academy Award–winning "Birdman or (The Unexpected Virtue of Ignorance)."
  • B. Myron Kerstein
    Myron Kerstein is an American film editor known for his work on acclaimed films and television projects, including the musical drama "Tick, Tick... Boom!".
  • C. Robert Leahy
    Robert Leahy is an American clinical psychologist and prominent cognitive therapist known for his work on anxiety, depression, and cognitive-behavioral therapy.
  • D. Eric Lamonsoff
    Eric Lamonsoff is a bumbling yet big-hearted family man and close friend of Lenny Feder in the Grown Ups comedy film series.
  • E. Michael Leibert
    Michael Leibert was an American theater director and producer best known for establishing the influential Berkeley Repertory Theatre in California.
  • 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_69ca84dc04488190b9c91193976c0960 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda214875481909f39e1d4dbac1fdb completed April 1, 2026, 10:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc4e30bc81909b1dce4a0cc69991 completed April 5, 2026, 2:43 a.m.
Created at: March 30, 2026, 8:28 p.m.