Triple

T11678815
Position Surface form Disambiguated ID Type / Status
Subject Baron Blood E277560 entity
Predicate stars P1956 FINISHED
Object Massimo Girotti E380059 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: Massimo Girotti | Statement: [Baron Blood, stars, Massimo Girotti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Massimo Girotti
Context triple: [Baron Blood, stars, Massimo Girotti]
  • A. Massimo Girotti chosen
    Massimo Girotti was an Italian actor known for his work in classic European cinema, including prominent roles in films by directors such as Luchino Visconti and Bernardo Bertolucci.
  • B. Massimo Gabutti
    Massimo Gabutti is an Italian music producer best known for his work in Eurodance and pop, including projects like Eiffel 65.
  • C. Livio Santini
    Livio Santini is an architect best known as a co-founder of the influential architecture firm Morphosis.
  • D. Giulio Berruti
    Giulio Berruti is an Italian actor and former fashion model known for his roles in romantic comedies and drama films.
  • E. Ermanno Cressoni
    Ermanno Cressoni was an influential Italian automobile designer best known for shaping Alfa Romeo’s distinctive angular design language in the 1970s and 1980s.
  • 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_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a46000a48190888ad1a6ade052e3 completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff8752207c81908369bce03b56b25e completed May 9, 2026, 7:13 p.m.
Created at: April 8, 2026, 9:40 p.m.