Triple

T4652919
Position Surface form Disambiguated ID Type / Status
Subject Pedro Muzquiz E102337 entity
Predicate portrayedInFilmBy P9616 FINISHED
Object Marco Leonardi E346458 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: Marco Leonardi | Statement: [Pedro Muzquiz, portrayedInFilmBy, Marco Leonardi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Marco Leonardi
Context triple: [Pedro Muzquiz, portrayedInFilmBy, Marco Leonardi]
  • A. Marco Leonardi chosen
    Marco Leonardi is an Italian actor known for his roles in films such as "Cinema Paradiso," "Like Water for Chocolate," and various international productions.
  • B. Marco Brambilla
    Marco Brambilla is an Italian-Canadian visual artist and filmmaker known for his elaborate video collages and for directing the sci-fi action film "Demolition Man."
  • C. Luca Calvani
    Luca Calvani is an Italian actor known for his work in film, television, and theater, including roles in international productions.
  • D. Luca Dotti
    Luca Dotti is an Italian author and graphic designer best known as the younger son of iconic actress Audrey Hepburn and Italian psychiatrist Andrea Dotti.
  • E. Leo Rossi
    Leo Rossi is an American character actor known for his supporting roles in crime dramas and thrillers in film and television.
  • 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_69bd43d71a308190afea7280841b0de8 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd6314883481908f085a7af497b0d8 completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69be1040dbdc8190b9ab7b0b58bca308 completed March 21, 2026, 3:28 a.m.
Created at: March 20, 2026, 1:14 p.m.