Triple

T14642036
Position Surface form Disambiguated ID Type / Status
Subject Once Upon a Time in America E343747 entity
Predicate editedBy P1954 FINISHED
Object Nino Baragli 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: Nino Baragli | Statement: [Once Upon a Time in America, editedBy, Nino Baragli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nino Baragli
Context triple: [Once Upon a Time in America, editedBy, Nino Baragli]
  • A. Nino Baragli chosen
    Nino Baragli was an Italian film editor renowned for his work on many classic films, particularly in collaboration with directors like Sergio Leone and Pier Paolo Pasolini.
  • B. Paolo Ajroldi
    Paolo Ajroldi is an advertising executive best known for co-founding the global marketing and communications agency TBWA Worldwide.
  • C. Giovanni Molari
    Giovanni Molari is an Italian academic and engineer who serves as rector of the historic University of Bologna.
  • D. Antonio Frova
    Antonio Frova was an Italian archaeologist best known for unearthing the Pilate Stone, a key inscription confirming the historical existence of Pontius Pilate.
  • E. Gabriele Baldini
    Gabriele Baldini was an Italian literary critic and scholar, known for his work on English literature and his marriage to writer Natalia Ginzburg.
  • 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_69d822e1a2cc81908e5bb93cf61ce3cc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4e80aa48190884bab800f357106 completed April 14, 2026, 9:43 p.m.
Created at: April 10, 2026, 1:26 a.m.