Triple

T22279386
Position Surface form Disambiguated ID Type / Status
Subject Avenida Brasília E550690 entity
Predicate locatedIn P40 FINISHED
Object Belém district 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: Belém district | Statement: [Avenida Brasília, locatedIn, Belém district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belém district
Context triple: [Avenida Brasília, locatedIn, Belém district]
  • A. Belém do Pará
    Belém do Pará is a major port city in northern Brazil, known as the gateway to the Amazon region and an important cultural and economic center.
  • B. Belém chosen
    Belém is a historic riverside district of Lisbon, Portugal, known for its monuments of the Age of Discoveries, including the Belém Tower and Jerónimos Monastery.
  • C. Ponto District
    Ponto District is an administrative district located within Huari Province in the Ancash Region of Peru.
  • D. Barra do Corda
    Barra do Corda is a municipality in the Brazilian state of Maranhão, known for its location in the interior region and its role as a local commercial and cultural center.
  • E. Graça district
    Graça district is a historic hilltop neighborhood in Lisbon, Portugal, known for its traditional atmosphere, viewpoints over the city, and classic tram connections.
  • 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_69e11e44d538819097c6b8f333af3352 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f14eaa8cec819081c2ad031154ebe7 completed April 29, 2026, 12:19 a.m.
Created at: April 16, 2026, 8:40 p.m.