Triple

T12768188
Position Surface form Disambiguated ID Type / Status
Subject Romeo & Juliet (2013 film) E305178 entity
Predicate director P255 FINISHED
Object Carlo Carlei 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: Carlo Carlei | Statement: [Romeo & Juliet (2013 film), director, Carlo Carlei]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carlo Carlei
Context triple: [Romeo & Juliet (2013 film), director, Carlo Carlei]
  • A. Carlo Carlei chosen
    Carlo Carlei is an Italian film director and screenwriter known for works such as the historical adventure film "The Last Legion" and the 2013 adaptation of "Romeo & Juliet."
  • B. Albano Carrisi
    Albano Carrisi is an Italian singer, actor, and winemaker best known as Al Bano, a popular figure in Italian pop and folk music since the late 1960s.
  • C. Carlo Rainaldi
    Carlo Rainaldi was a prominent 17th-century Italian Baroque architect known for designing several major churches and urban monuments in Rome.
  • D. Tullio Pizzorno
    Tullio Pizzorno is an individual notable enough to be recognized as a prominent bearer of the given name Tullio.
  • E. Franco Arcalli
    Franco Arcalli was an Italian film editor and screenwriter known for his innovative work on influential European art films of the 1960s and 1970s.
  • 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_69d7bdf2b43c819098ae5aa68e61ea58 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96df3b2f88190b37b696400178795 completed April 10, 2026, 9:38 p.m.
Created at: April 9, 2026, 5:28 p.m.