Triple
T22995835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metrô do Recife |
E572186
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Cajueiro Seco Station |
—
|
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: Cajueiro Seco Station | Statement: [Metrô do Recife, hasStation, Cajueiro Seco Station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cajueiro Seco Station Context triple: [Metrô do Recife, hasStation, Cajueiro Seco Station]
-
A.
Cajueiro Seco Station
chosen
Cajueiro Seco Station is a terminal station on the Recife Metro system in the Recife metropolitan area of Brazil.
-
B.
Caieiras station
Caieiras station is a commuter rail station in the municipality of Caieiras, São Paulo, serving passengers on the CPTM suburban rail network.
-
C.
Sacomã station
Sacomã station is a metro station in São Paulo, Brazil, serving the southeastern area of the city and connecting the Ipiranga district with the broader São Paulo Metro network.
-
D.
Rio Grande da Serra station
Rio Grande da Serra station is a commuter rail terminus in the São Paulo metropolitan region, serving as the endpoint of CPTM’s Line 10–Turquesa.
-
E.
Joana Bezerra Station
Joana Bezerra Station is a major urban rail station in Recife, Brazil, serving as an important hub in the Metrô do Recife network.
- 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.