Triple

T2539592
Position Surface form Disambiguated ID Type / Status
Subject Antonio E56351 entity
Predicate hasDiminutive P456 FINISHED
Object Toni E150885 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: Toni | Statement: [Antonio, hasDiminutive, Toni]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toni
Context triple: [Antonio, hasDiminutive, Toni]
  • A. Toni chosen
    Toni is a common diminutive given name, typically used as a shorter or more familiar form of names like Anton, Anthony, or Antonia.
  • B. Tina
    Tina is the nickname of Tina Fey, an American comedian, writer, actress, and producer best known for her work on Saturday Night Live and 30 Rock.
  • C. Tina
    Tina, formally known as Baroness Stowell of Beeston, is a British Conservative politician and life peer in the House of Lords.
  • D. Toni Vega
    Toni Vega is a musical artist known for contributing featured vocals to tracks such as "Monkey Business."
  • E. Tiffani
    Tiffani is a given name, typically a modern variant of the name Tiffany used for girls.
  • 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_69ab4a49b6508190bc467fbef4bac334 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd29b44448190ba4f82b0c1425f21 completed March 7, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69af5cff8d188190844b177b5d3952b0 completed March 9, 2026, 11:51 p.m.
Created at: March 6, 2026, 9:47 p.m.