Triple

T18696936
Position Surface form Disambiguated ID Type / Status
Subject Conservatorio di Pesaro E457142 entity
Predicate notableAlumnus P304 FINISHED
Object Mario Del Monaco 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: Mario Del Monaco | Statement: [Conservatorio di Pesaro, notableAlumnus, Mario Del Monaco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mario Del Monaco
Context triple: [Conservatorio di Pesaro, notableAlumnus, Mario Del Monaco]
  • A. Mario Del Monaco chosen
    Mario Del Monaco was a renowned Italian dramatic tenor celebrated for his powerful voice and intense performances, particularly in the Italian operatic repertoire.
  • B. Umberto Martini
    Umberto Martini is an Italian academic and tourism expert known for his work in marketing and destination management.
  • C. Fausto Russo Alesi
    Fausto Russo Alesi is an Italian actor known for his work in contemporary Italian cinema and theater, including roles in acclaimed crime and drama films.
  • D. Luigi Martini
    Luigi Martini is an individual notable enough to be recognized as a namesake or prominent bearer of the surname Martini.
  • E. Roberto De Angelis
    Roberto De Angelis is a cinematographer known for his work on major feature films, including the action-comedy sequel "Bad Boys for Life."
  • 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_69d8d392aad081909fe31aa03e6e97d1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e562e8bc408190ab41b3c21003c249 completed April 19, 2026, 11:19 p.m.
Created at: April 10, 2026, 11:49 a.m.