Triple
T22995819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metrô do Recife |
E572186
|
entity |
| Predicate | cityServed |
P82
|
FINISHED |
| Object | Ipojuca |
—
|
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: Ipojuca | Statement: [Metrô do Recife, cityServed, Ipojuca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ipojuca Context triple: [Metrô do Recife, cityServed, Ipojuca]
-
A.
Ipojuca
chosen
Ipojuca is a coastal municipality in northeastern Brazil known for its tourism-driven economy and famous beaches such as Porto de Galinhas.
-
B.
Itapecuru-Mirim
Itapecuru-Mirim is a municipality in the Brazilian state of Maranhão, known for its historical colonial architecture and its location along the Itapecuru River.
-
C.
Sertãozinho
Sertãozinho is a municipality in the interior of Brazil known for its strong sugarcane-based agribusiness and ethanol production.
-
D.
Itapipoca
Itapipoca is a municipality in the northeastern Brazilian state of Ceará, known for its diverse landscapes that include beaches, mountains, and semi-arid hinterlands.
-
E.
Caraguatatuba
Caraguatatuba is a coastal city in the state of São Paulo, Brazil, known for its beaches and role as a popular tourist destination on the northern coast.
- 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.