Triple

T10493713
Position Surface form Disambiguated ID Type / Status
Subject Dressed to Kill E247481 entity
Predicate composer P1361 FINISHED
Object Pino Donaggio E848089 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: Pino Donaggio | Statement: [Dressed to Kill, composer, Pino Donaggio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pino Donaggio
Context triple: [Dressed to Kill, composer, Pino Donaggio]
  • A. Pino Donaggio chosen
    Pino Donaggio is an Italian composer best known for his atmospheric film scores, particularly in the horror and thriller genres.
  • B. Nicola Piovani
    Nicola Piovani is an Italian composer and pianist best known for his film scores, including the Academy Award–winning music for "Life Is Beautiful."
  • C. Sergio Silvestri
    Sergio Silvestri is an individual notable enough to be recognized as a prominent bearer of the surname Silvestri.
  • D. Nino Rota
    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.
  • E. 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."
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5097fe2bc81909d66ce43f3533284 completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dcaeb6088190829b6c26eb1de7d5 completed April 10, 2026, 11:19 a.m.
Created at: April 6, 2026, 12:24 p.m.