Triple

T23121042
Position Surface form Disambiguated ID Type / Status
Subject Eight Men Out E576891 entity
Predicate castMember P1668 FINISHED
Object Michael Lerner 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 Lerner | Statement: [Eight Men Out, castMember, Michael Lerner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Lerner
Context triple: [Eight Men Out, castMember, Michael Lerner]
  • A. Michael Lerner chosen
    Michael Lerner was an American character actor known for his prolific film and television career, including an Academy Award–nominated role in "Barton Fink."
  • B. Michael Alan Lerner
    Michael Alan Lerner is an American screenwriter best known for co-writing the acclaimed biographical drama film "Love & Mercy" about Beach Boys leader Brian Wilson.
  • C. Michele Lerner
    Michele Lerner is known primarily as the third wife of American lyricist and playwright Alan Jay Lerner.
  • D. John Leventhal
    John Leventhal is an American guitarist, producer, and songwriter known for his acclaimed work in Americana and country music, including long-time collaborations with Rosanne Cash.
  • E. Jeffrey Lerner
    Jeffrey Lerner is a film and television producer known for his work as an executive producer on various projects, including the movie "Watch Over Me."
  • 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_69e245f6c2e881909a228fdcfeb7c7d3 completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f18e4f9be881908307838bfb5edc0c completed April 29, 2026, 4:51 a.m.
Created at: April 17, 2026, 3:59 p.m.