Triple

T11893435
Position Surface form Disambiguated ID Type / Status
Subject Campeonato Paulista E282975 entity
Predicate alsoKnownAs P39 FINISHED
Object Paulistão E282975 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: Paulistão | Statement: [Campeonato Paulista, alsoKnownAs, Paulistão]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paulistão
Context triple: [Campeonato Paulista, alsoKnownAs, Paulistão]
  • A. Campeonato Paulista chosen
    Campeonato Paulista is the top professional football championship of the Brazilian state of São Paulo, featuring its major clubs in an annual competition.
  • B. Paulista
    Paulista is a coastal city in the northeastern Brazilian state of Pernambuco, known for its beaches and proximity to the Recife metropolitan area.
  • C. União São João
    União São João is a Brazilian football club based in Araras, São Paulo, known for having developed and featured notable players such as Roberto Carlos.
  • D. Portuguesa Santista
    Portuguesa Santista is a Brazilian football club based in Santos, São Paulo, known for its youth development and regional tradition.
  • E. Jaguariúna
    Jaguariúna is a municipality in southeastern Brazil known for its agribusiness, technology industries, and popular rodeo festival.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8dd1172988190a2c13d37220f2f93 completed April 10, 2026, 11:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69f4180569ac81909137d56374e800c0 completed May 1, 2026, 3:03 a.m.
Created at: April 8, 2026, 9:44 p.m.