Triple

T13700713
Position Surface form Disambiguated ID Type / Status
Subject Pericle il nero E328508 entity
Predicate screenwriter P2831 FINISHED
Object Stefano Mordini E1096195 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: Stefano Mordini | Statement: [Pericle il nero, screenwriter, Stefano Mordini]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stefano Mordini
Context triple: [Pericle il nero, screenwriter, Stefano Mordini]
  • A. Stefano Mordini chosen
    Stefano Mordini is an Italian film director and screenwriter known for his gritty, character-driven dramas.
  • B. Stefano Pessina
    Stefano Pessina is an Italian-Monegasque billionaire businessman best known as the longtime leader and major shareholder behind the global pharmacy and retail group Walgreens Boots Alliance.
  • C. Filippo Barigioni
    Filippo Barigioni was an Italian Baroque architect and sculptor active in Rome in the early 18th century, known for his work on churches, fountains, and urban spaces.
  • D. Stefano Arnaldi
    Stefano Arnaldi is a composer best known for creating the musical score for the film "Tea with Mussolini."
  • E. Fabrizio Ravanelli
    Fabrizio Ravanelli is a retired Italian striker known for his prolific goal scoring in the 1990s, including spells at clubs such as Juventus, Middlesbrough, and Lazio, and for winning the UEFA Champions League with Juventus.
  • 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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc879adc88190b03f1cf815b71061 completed April 12, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd54f748d481909661deb151da34c1 completed May 8, 2026, 3:13 a.m.
Created at: April 9, 2026, 9:54 p.m.