Triple

T20160166
Position Surface form Disambiguated ID Type / Status
Subject Enzo E491680 entity
Predicate hasVariant P455 FINISHED
Object Enzo (Spanish usage) 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: Enzo (Spanish usage) | Statement: [Enzo, hasVariant, Enzo (Spanish usage)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Enzo (Spanish usage)
Context triple: [Enzo, hasVariant, Enzo (Spanish usage)]
  • A. Enzo chosen
    Enzo is an Italian given name commonly used as a standalone name and also as a diminutive or short form of longer names like Vincenzo or Lorenzo.
  • B. Spagnuolo
    Spagnuolo is the surname of Steve Spagnuolo, an American football coach best known as the defensive coordinator for multiple Super Bowl–winning teams.
  • C. Gianfranco
    Gianfranco is an Italian masculine given name commonly associated with notable figures in fashion, sports, and the arts.
  • D. Giancarlo
    Giancarlo is an Italian masculine given name commonly used in Italy and among Italian communities worldwide.
  • E. Sergio
    Sergio is a masculine given name commonly used in Spanish and Italian-speaking countries, derived from the Latin name Sergius.
  • 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_69da6266c6888190bc1a3ecf24814d34 completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e667e37c8c8190827839291027d9e2 completed April 20, 2026, 5:52 p.m.
Created at: April 11, 2026, 11:34 p.m.