Triple

T20080677
Position Surface form Disambiguated ID Type / Status
Subject Snake Eyes E499990 entity
Predicate producer P490 FINISHED
Object Lorenzo di Bonaventura 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: Lorenzo di Bonaventura | Statement: [Snake Eyes, producer, Lorenzo di Bonaventura]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lorenzo di Bonaventura
Context triple: [Snake Eyes, producer, Lorenzo di Bonaventura]
  • A. Lorenzo di Bonaventura chosen
    Lorenzo di Bonaventura is an American film producer best known for overseeing major Hollywood action and franchise films, including the Transformers series.
  • B. Ciro Ferrara
    Ciro Ferrara is a former Italian footballer and defender best known for his successful club career with Napoli and Juventus as well as his appearances for the Italian national team.
  • C. Lorenzo Carcaterra
    Lorenzo Carcaterra is an American writer and former journalist best known for his gritty crime novels and memoirs, including the book that inspired the film "Sleepers."
  • D. Leo Benvenuti
    Leo Benvenuti is an American screenwriter best known for co-writing popular family comedies such as "The Santa Clause" and "Kicking & Screaming."
  • E. Lorenzo Marinelli
    Lorenzo Marinelli is an editor known for his work on the film "The Changeling."
  • 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66557c19c8190b511857490bbd423 completed April 20, 2026, 5:41 p.m.
Created at: April 11, 2026, 3:41 p.m.