Triple
T18822464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paraná |
E460294
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | São José dos Pinhais |
E652872
|
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: São José dos Pinhais | Statement: [Paraná, hasCity, São José dos Pinhais]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: São José dos Pinhais Context triple: [Paraná, hasCity, São José dos Pinhais]
-
A.
São José dos Pinhais
chosen
São José dos Pinhais is an industrial and logistics hub in the Curitiba metropolitan area of Paraná, Brazil, known for its automotive plants and proximity to the region’s main international airport.
-
B.
Guarapuava
Guarapuava is a city in the state of Paraná, Brazil, known for its significant population of German Brazilians and its role as an agricultural and regional economic center.
-
C.
Curití
Curití is a small Colombian town in the Santander Department, known for its colonial architecture, natural landscapes, and traditional crafts.
-
D.
Maringá
Maringá is a planned, mid-20th-century city in the state of Paraná known for its green urban design, strong agricultural-based economy, and high quality of life.
-
E.
Osasco
Osasco is a major industrial and commercial city in the metropolitan region of São Paulo, Brazil.
- 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_69d8dcf94c288190a06dea029ae4b223 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a6bbc7148190819252071a765975 |
completed | April 20, 2026, 4:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0590fe846c8190a2d31f7b847382e5 |
completed | May 14, 2026, 9:08 a.m. |
Created at: April 10, 2026, 11:55 a.m.