Triple

T14167504
Position Surface form Disambiguated ID Type / Status
Subject Voices E351116 entity
Predicate cinematography P1953 FINISHED
Object Mario Tosi E453304 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: Mario Tosi | Statement: [Voices, cinematography, Mario Tosi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mario Tosi
Context triple: [Voices, cinematography, Mario Tosi]
  • A. Mario Tosi chosen
    Mario Tosi is an Italian-born cinematographer known for his work on several notable American films in the 1970s and 1980s.
  • B. Mario Girotti
    Mario Girotti is the birth name of Italian actor Terence Hill, famed for his spaghetti westerns and action-comedy films, often alongside Bud Spencer.
  • C. Mario Palanti
    Mario Palanti was an Italian architect best known for his monumental eclectic skyscrapers in South America, particularly in Buenos Aires and Montevideo.
  • D. Mario Nascimbene
    Mario Nascimbene was an Italian film composer renowned for his innovative scores for both European cinema and major Hollywood productions in the mid-20th century.
  • E. Mario Lanfranchi
    Mario Lanfranchi was an Italian film and television director and producer, known for his work in opera productions and for his marriage to soprano Anna Moffo.
  • 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_69d8278775fc8190b0802d22ca2f495d completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61b355f08190864c7322bbcb766d completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe9db6187c8190969b035bc2813413 completed May 9, 2026, 2:36 a.m.
Created at: April 10, 2026, 1 a.m.