Triple

T13346921
Position Surface form Disambiguated ID Type / Status
Subject Michael V. Gazzo E317976 entity
Predicate name P16 FINISHED
Object Michael V. Gazzo E317976 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 V. Gazzo | Statement: [Michael V. Gazzo, name, Michael V. Gazzo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael V. Gazzo
Context triple: [Michael V. Gazzo, name, Michael V. Gazzo]
  • A. Michael V. Gazzo chosen
    Michael V. Gazzo was an American actor and playwright best known for his Oscar-nominated performance as Frank Pentangeli in *The Godfather Part II* and for writing the play *A Hatful of Rain*.
  • B. John DiFronzo
    John DiFronzo was an American mobster who rose to become a powerful boss of the Chicago Outfit and a prominent figure in organized crime.
  • C. Michael De Luca
    Michael De Luca is an American film producer and studio executive known for overseeing and producing a wide range of major Hollywood films across genres.
  • D. Edward Carfagno
    Edward Carfagno was an American art director and production designer known for his work on numerous major Hollywood films, including several Oscar-winning productions.
  • E. John Fusco
    John Fusco is an American screenwriter and producer best known for writing Western-themed films such as "Young Guns" and creating the Netflix series "Marco Polo."
  • 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_69d806b5a3c08190b42c267fb092f98a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99e89c65c819093f3bea11d6073c5 completed April 11, 2026, 1:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69fea598fd888190b53ab937bad1d824 completed May 9, 2026, 3:10 a.m.
Created at: April 9, 2026, 9:31 p.m.