Triple
T18628099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BR-277 |
E455335
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object | Guarapuava |
—
|
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: Guarapuava | Statement: [BR-277, passesThrough, Guarapuava]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guarapuava Context triple: [BR-277, passesThrough, Guarapuava]
-
A.
Guarapuava
chosen
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.
-
B.
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.
-
C.
Mourão
Mourão is a small municipality in Portugal’s Alentejo region, known for its historic castle and proximity to the Alqueva Reservoir.
-
D.
Guaratinguetá
Guaratinguetá is a historic municipality in southeastern Brazil known for its colonial heritage and religious tourism, located in the state of São Paulo.
-
E.
Água Grande
Água Grande is an administrative district that includes São Tomé, the capital city of São Tomé and Príncipe, on the island of São Tomé.
- 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_69d8d38cc7948190a55ea64e5638994e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54f063a1c819087e544c64f5cf80f |
completed | April 19, 2026, 9:54 p.m. |
Created at: April 10, 2026, 11:46 a.m.