Triple

T8795870
Position Surface form Disambiguated ID Type / Status
Subject Arena da Baixada E209286 entity
Predicate knownAs P39 FINISHED
Object Arena da Baixada E209286 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: Arena da Baixada | Statement: [Arena da Baixada, knownAs, Arena da Baixada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arena da Baixada
Context triple: [Arena da Baixada, knownAs, Arena da Baixada]
  • A. Arena da Baixada chosen
    Arena da Baixada is a modern football stadium in Curitiba, Brazil, best known internationally for hosting matches during the 2014 FIFA World Cup.
  • B. Ourinhos
    Ourinhos is a municipality in the southwestern part of the state of São Paulo, Brazil, known as a regional commercial and agricultural center.
  • C. Vitória de Santo Antão
    Vitória de Santo Antão is a municipality in northeastern Brazil known for its sugarcane-based economy, cachaça production, and colonial-era heritage.
  • D. Maracanaú
    Maracanaú is an industrial and residential city in northeastern Brazil, located in the metropolitan region of Fortaleza in the state of Ceará.
  • E. Envigado
    Envigado is a city in northwestern Colombia that forms part of the Medellín metropolitan area and is known for its residential character and quality of life.
  • 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_69ca836240888190a62b262e56a69d2f completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fa24ca08190a7738a7f1c446456 completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6f5d655881909013ac3e2ac0cebb completed April 3, 2026, 7:42 a.m.
Created at: March 30, 2026, 6:44 p.m.