Triple

T13519693
Position Surface form Disambiguated ID Type / Status
Subject Romeo and Juliet (1968 film) E322860 entity
Predicate producer P490 FINISHED
Object Franco Zeffirelli E251656 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: Franco Zeffirelli | Statement: [Romeo and Juliet (1968 film), producer, Franco Zeffirelli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Franco Zeffirelli
Context triple: [Romeo and Juliet (1968 film), producer, Franco Zeffirelli]
  • A. Franco Zeffirelli chosen
    Franco Zeffirelli was an Italian director and producer renowned for his lavish film and opera adaptations of classic works, including Shakespearean dramas and grand operatic productions.
  • B. Gabriele Muccino
    Gabriele Muccino is an Italian film director known internationally for his emotionally driven dramas, including collaborations with Will Smith.
  • C. Ron Winston
    Ron Winston was a television director best known for his work on classic anthology series such as The Twilight Zone.
  • D. Hugh Hudson
    Hugh Hudson was a British film director best known for his Academy Award–winning 1981 sports drama "Chariots of Fire."
  • E. Roger Michell
    Roger Michell was a British film and theatre director best known for his acclaimed romantic comedies and character-driven dramas, including the hit film "Notting Hill."
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafa3df0c8190804174695587f0ea completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75d93a2608190a3a693bf4086a010 completed May 3, 2026, 2:37 p.m.
Created at: April 9, 2026, 9:44 p.m.