Triple

T22995791
Position Surface form Disambiguated ID Type / Status
Subject Joana Bezerra metro station E572185 entity
Predicate partOf P40 FINISHED
Object Recife Metro 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: Recife Metro | Statement: [Joana Bezerra metro station, partOf, Recife Metro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Recife Metro
Context triple: [Joana Bezerra metro station, partOf, Recife Metro]
  • A. Metrô do Recife chosen
    Metrô do Recife is the urban rail transit system serving the metropolitan area of Recife, Brazil.
  • B. Rio de Janeiro Metro
    The Rio de Janeiro Metro is the rapid transit system serving the city of Rio de Janeiro, Brazil, providing high-capacity urban rail transport across key neighborhoods and metropolitan areas.
  • C. Brasília Metro
    The Brasília Metro is the rapid transit system serving Brazil’s capital, connecting key government, residential, and commercial areas across the Federal District.
  • D. BRT TransCarioca
    BRT TransCarioca is a bus rapid transit corridor in Rio de Janeiro that connects key neighborhoods and the international airport, improving high-capacity public transportation across the city.
  • E. São Paulo Metro
    The São Paulo Metro is a major rapid transit system serving the city of São Paulo, Brazil, known for its extensive network, high ridership, and role as a backbone of the city's public transportation.
  • 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_69e245b535808190adef8a9df3c584db completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f182f3186c81909e0d5177029a72ae completed April 29, 2026, 4:02 a.m.
Created at: April 17, 2026, 3:50 p.m.