Triple

T22885447
Position Surface form Disambiguated ID Type / Status
Subject Nenê E567591 entity
Predicate nickname P55 FINISHED
Object Nenê 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: Nenê | Statement: [Nenê, nickname, Nenê]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nenê
Context triple: [Nenê, nickname, Nenê]
  • A. Nenê chosen
    Nenê is a Brazilian professional basketball player and longtime NBA center known for his physical interior play and key contributions to both the Denver Nuggets and Washington Wizards.
  • B. Nena
    Nena is a German pop singer and actress best known internationally for her 1983 hit song "99 Luftballons."
  • C. Nilsa
    Nilsa is a feminine given name of Spanish origin, often used in Latin American countries.
  • D. Ninna
    Ninna was a Japanese era name (nengō) of the Heian period, used during the reign of Emperor Uda.
  • E. Nenita
    Nenita is a village on the Greek island of Chios, known for its traditional mastic cultivation and characteristic island architecture.
  • 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_69e2458a92ec81908fc1cd5f6407d2ab completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17fc0cdb081908107d40069d9735f completed April 29, 2026, 3:49 a.m.
Created at: April 17, 2026, 3:40 p.m.