Triple

T12314021
Position Surface form Disambiguated ID Type / Status
Subject Line 7-Rubi E293551 entity
Predicate hasStation P35 FINISHED
Object Jundiaí station E996209 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: Jundiaí station | Statement: [Line 7-Rubi, hasStation, Jundiaí station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jundiaí station
Context triple: [Line 7-Rubi, hasStation, Jundiaí station]
  • A. Jundiaí station chosen
    Jundiaí station is a major railway terminus in the city of Jundiaí, São Paulo, serving as an important hub in the São Paulo metropolitan rail network.
  • B. Campo Limpo station
    Campo Limpo station is a metro station on São Paulo’s Line 5–Lilac, serving the Campo Limpo district in the city’s south zone.
  • C. Santo Amaro station
    Santo Amaro station is a major interchange station in São Paulo’s metro network, connecting Line 5–Lilac with other urban rail services.
  • D. Campo Belo station
    Campo Belo station is an underground metro station in São Paulo, Brazil, serving the city’s Line 5–Lilac.
  • E. Capão Redondo station
    Capão Redondo station is a metro terminus in São Paulo, Brazil, serving the southern region of the city on Line 5–Lilac.
  • 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_69d6ab6a2b50819082f6aedd32ed608a completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f03d3c88190baedffb83465bff8 completed April 10, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68ea215a4819090cea3184f3a231c completed May 2, 2026, 11:54 p.m.
Created at: April 8, 2026, 9:53 p.m.