Triple
T21983803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nova Cruz microregion |
E542904
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Várzea, Rio Grande do Norte |
—
|
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: Várzea, Rio Grande do Norte | Statement: [Nova Cruz microregion, hasSettlement, Várzea, Rio Grande do Norte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Várzea, Rio Grande do Norte Context triple: [Nova Cruz microregion, hasSettlement, Várzea, Rio Grande do Norte]
-
A.
Várzea, Rio Grande do Norte
chosen
Várzea, Rio Grande do Norte is a small municipality in the state of Rio Grande do Norte in Brazil’s Northeast region.
-
B.
Várzea da Igreja
Várzea da Igreja is a small settlement located in the municipality of São Domingos.
-
C.
Brejo de Beberibe
Brejo de Beberibe is a neighborhood within the city of Recife in the state of Pernambuco, Brazil.
-
D.
Brejo Grande
Brejo Grande is a small coastal municipality in the Brazilian state of Sergipe, known for its location at the mouth of the São Francisco River.
-
E.
Várzea Paulista
Várzea Paulista is a municipality in southeastern Brazil known for its integration into the industrial and services corridor of the São Paulo metropolitan region.
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f12708055c8190b626ce244e368296 |
completed | April 28, 2026, 9:30 p.m. |
Created at: April 16, 2026, 8:04 p.m.