Triple

T7259654
Position Surface form Disambiguated ID Type / Status
Subject Southern Brazil E159616 entity
Predicate hasMajorCity P316 FINISHED
Object Londrina E438769 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: Londrina | Statement: [Southern Brazil, hasMajorCity, Londrina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Londrina
Context triple: [Southern Brazil, hasMajorCity, Londrina]
  • A. Londrina chosen
    Londrina is a major city in the southern Brazilian state of Paraná known for its significant Japanese Brazilian community and strong agricultural-based economy.
  • B. Uberlândia
    Uberlândia is a major commercial and logistics hub in the Brazilian state of Minas Gerais, known for its agribusiness, services sector, and strategic location in the country's Southeast.
  • C. Cuiabá
    Cuiabá is the capital city of Brazil’s Mato Grosso state and a primary urban hub and access point for exploring the Pantanal wetlands.
  • D. Vitória
    Vitória is the capital city of the Brazilian state of Espírito Santo, known for its coastal setting, port activities, and surrounding islands.
  • E. Vitória
    Vitória is a traditional Brazilian football club from Salvador, Bahia, best known for its intense local rivalry with Esporte Clube Bahia in the Ba–Vi derby.
  • 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_69c68838f9948190875fd60b2351230c completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eac5311c819094fc6880f3152813 completed March 27, 2026, 8:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d3bda4808190810f2d170cb693b9 completed March 28, 2026, 1:12 p.m.
Created at: March 27, 2026, 2:57 p.m.