Triple

T16133668
Position Surface form Disambiguated ID Type / Status
Subject The Leopard E391466 entity
Predicate musicBy P1952 FINISHED
Object Nino Rota E50629 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: Nino Rota | Statement: [The Leopard, musicBy, Nino Rota]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nino Rota
Context triple: [The Leopard, musicBy, Nino Rota]
  • A. Nino Rota chosen
    Nino Rota was an Italian composer best known for his iconic film scores, including his collaborations with Federico Fellini and his music for The Godfather.
  • B. Franco Silvestri
    Franco Silvestri is an individual notable enough to be recognized as a prominent bearer of the surname Silvestri.
  • C. Luis Bacalov
    Luis Bacalov was an Argentine-Italian composer and pianist renowned for his film scores, particularly in Italian cinema and Spaghetti Westerns, and for winning an Academy Award for Best Original Dramatic Score.
  • D. Ennio Morricone
    Ennio Morricone was an Italian composer and conductor renowned for his iconic film scores, particularly for Spaghetti Westerns like "The Good, the Bad and the Ugly."
  • E. Pino Donaggio
    Pino Donaggio is an Italian composer best known for his atmospheric film scores, particularly in the horror and thriller genres.
  • 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_69d87f1bb0988190b490d273dbf3fd03 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21a039f0c8190a679e16a27f2dbe3 completed April 17, 2026, 11:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7a304348190bf471f2b9279b806 completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 5:01 a.m.