Triple

T16229029
Position Surface form Disambiguated ID Type / Status
Subject 88 Minutes E393930 entity
Predicate producer P490 FINISHED
Object Avi Lerner E303929 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: Avi Lerner | Statement: [88 Minutes, producer, Avi Lerner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Avi Lerner
Context triple: [88 Minutes, producer, Avi Lerner]
  • A. Avi Lerner chosen
    Avi Lerner is an Israeli-American film producer and founder of Millennium Films, known for financing and producing numerous action movies and franchises.
  • B. Avi Dichter
    Avi Dichter is an Israeli politician and former head of the Shin Bet security service who has held several senior government positions, including serving as Minister of Internal Security (Police).
  • C. Avi Rothman
    Avi Rothman is an American actor, writer, and comedian known for his work in film and television and for being married to actress and comedian Kristen Wiig.
  • D. Avi Goldstein
    Avi Goldstein is an individual notable enough to be recognized as a prominent bearer of the surname Goldstein.
  • E. Avi Belleli
    Avi Belleli is an Israeli composer and musician best known for his atmospheric scores for film and television, including the acclaimed series "Prisoners of War."
  • 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_69d87f204df88190a8f88923decf9835 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e23d2889688190ac04e4e9479cabf4 completed April 17, 2026, 2:01 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017ab10a48190afa19e74c0059427 completed May 10, 2026, 5:29 a.m.
Created at: April 10, 2026, 5:03 a.m.