Triple

T15554683
Position Surface form Disambiguated ID Type / Status
Subject Goiás E370836 entity
Predicate historicalCapital P2536 FINISHED
Object Goiás (city) E1169219 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: Goiás (city) | Statement: [Goiás, historicalCapital, Goiás (city)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Goiás (city)
Context triple: [Goiás, historicalCapital, Goiás (city)]
  • A. Goiás (city) chosen
    Goiás (city) is a historic colonial town in central Brazil, renowned for its well-preserved architecture and status as a UNESCO World Heritage Site.
  • B. Goiânia
    Goiânia is the capital and largest city of the Brazilian state of Goiás, known as a major regional center for agriculture, industry, and services in central Brazil.
  • C. Aparecida de Goiânia
    Aparecida de Goiânia is a major city in central Brazil, forming part of the metropolitan area of Goiânia in the state of Goiás.
  • D. Garça
    Garça is the Portuguese term for a heron, a long-legged wading bird commonly found near wetlands and waterways.
  • E. Guarulhos
    Guarulhos is a major city in the São Paulo metropolitan area of Brazil, known as an important industrial and logistics hub.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04a96c0c88190808f68601a36b506 completed April 16, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ec93ac48190b2548a61797480cc completed May 9, 2026, 5:28 p.m.
Created at: April 10, 2026, 4:09 a.m.