Triple

T14128854
Position Surface form Disambiguated ID Type / Status
Subject Joely Richardson E340106 entity
Predicate sibling P363 FINISHED
Object Carlo Gabriel Nero E331538 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: Carlo Gabriel Nero | Statement: [Joely Richardson, sibling, Carlo Gabriel Nero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carlo Gabriel Nero
Context triple: [Joely Richardson, sibling, Carlo Gabriel Nero]
  • A. Carlo Gabriel Nero chosen
    Carlo Gabriel Nero is an Italian-British film director and screenwriter known for his work on independent films and for being part of a prominent acting family.
  • B. Luciano
    Luciano is a masculine given name of Italian origin, famously borne by the renowned operatic tenor Luciano Pavarotti.
  • C. Antonio Contino
    Antonio Contino was a Venetian architect best known for designing the iconic Bridge of Sighs in Venice, Italy.
  • D. Guido Caroli
    Guido Caroli was an Italian speed skater best known for lighting the Olympic cauldron at the 1956 Winter Olympics in Cortina d'Ampezzo.
  • E. Leo Catozzo
    Leo Catozzo was an Italian film editor and inventor best known for his influential work in post-war Italian cinema and for creating the Catozzo splicing machine used worldwide in film editing.
  • 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_69d81c6a95b481909e39111e0c1f31ee completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de6098013c8190b1bac9d3fff60acd completed April 14, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcf7e2b0248190ba40aa8395355052 completed May 7, 2026, 8:36 p.m.
Created at: April 9, 2026, 10:23 p.m.