Triple
T7259656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Brazil |
E159616
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Blumenau |
E278154
|
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: Blumenau | Statement: [Southern Brazil, hasMajorCity, Blumenau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blumenau Context triple: [Southern Brazil, hasMajorCity, Blumenau]
-
A.
Blumenau
chosen
Blumenau is a city in southern Brazil known for its strong German cultural heritage, architecture, and one of the world’s largest Oktoberfest celebrations.
-
B.
Brusque
Brusque is a city in the Brazilian state of Santa Catarina known for its strong German-Brazilian heritage and textile industry.
-
C.
Jaraguá do Sul
Jaraguá do Sul is a city in southern Brazil known for its strong German-Brazilian cultural heritage and industrial economy.
-
D.
Itajaí
Itajaí is a coastal city in the Brazilian state of Santa Catarina known for its strong German-Brazilian cultural heritage and important Atlantic port.
-
E.
Florianópolis
Florianópolis is the capital city of the Brazilian state of Santa Catarina, known for its numerous beaches, tourism, and high quality of life.
- 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_69c68838f9948190875fd60b2351230c |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eac5311c819094fc6880f3152813 |
completed | March 27, 2026, 8:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7db175b188190beb5ba5ebb662c9b |
completed | March 28, 2026, 1:43 p.m. |
Created at: March 27, 2026, 2:57 p.m.