Triple

T6189398
Position Surface form Disambiguated ID Type / Status
Subject Vanessa Redgrave E138147 entity
Predicate child P120 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: [Vanessa Redgrave, child, Carlo Gabriel Nero]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carlo Gabriel Nero
Context triple: [Vanessa Redgrave, child, 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. 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.
  • D. Leonardo Bravo
    Leonardo Bravo was a prominent insurgent leader in Mexico’s War of Independence, known for his role alongside José María Morelos in key campaigns against Spanish royalist forces.
  • E. Renato
    Renato is a masculine given name of Latin origin, commonly used in Italian, Portuguese, and Spanish-speaking countries.
  • 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_69c008a8fd408190b7ec6e42934974a6 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062192c5481909eb41f8c5d1208a3 completed March 22, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20d86da748190932c68d415dea01d completed March 24, 2026, 4:05 a.m.
Created at: March 22, 2026, 4:19 p.m.