Triple
T22431357
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Potiguar |
E554506
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object | Florânia |
—
|
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: Florânia | Statement: [Central Potiguar, containsMunicipality, Florânia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Florânia Context triple: [Central Potiguar, containsMunicipality, Florânia]
-
A.
Florânia
chosen
Florânia is a municipality in the state of Rio Grande do Norte in Brazil, known for its semi-arid landscape and small-town character within the Central Potiguar region.
-
B.
Flores da Cunha
Flores da Cunha is a Brazilian municipality in the Serra Gaúcha region of Rio Grande do Sul, known for its strong Italian heritage and wine production.
-
C.
Grajaú
Grajaú is a municipality in the Brazilian state of Maranhão, known for its regional agriculture and position in the northeastern interior of the country.
-
D.
Arujá
Arujá is a municipality in the state of São Paulo, Brazil, known for its green areas and residential character within the Greater São Paulo region.
-
E.
Itacoatiara
Itacoatiara is a significant river port city in the Brazilian state of Amazonas, located along the Amazon River and serving as an important regional commercial and transportation hub.
- 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_69e11e4f2d0c819091aa3558ea2ee630 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a32139481909baaf9275f5e0257 |
completed | April 29, 2026, 1:09 a.m. |
Created at: April 16, 2026, 8:47 p.m.