Triple
T21532969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brazilian Midwest |
E531280
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Anápolis |
—
|
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: Anápolis | Statement: [Brazilian Midwest, containsCity, Anápolis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anápolis Context triple: [Brazilian Midwest, containsCity, Anápolis]
-
A.
Anápolis
chosen
Anápolis is a city in the state of Goiás, Brazil, known as an important industrial and logistics hub in the country’s Central-West region.
-
B.
Morada Nova
Morada Nova is a municipality in the state of Ceará in northeastern Brazil, known for its agricultural activities and semi-arid landscape.
-
C.
Caldas Novas
Caldas Novas is a Brazilian resort city famous for its extensive natural hot springs and thermal tourism, located in the state of Goiás.
-
D.
Sete Lagoas
Sete Lagoas is a city in the state of Minas Gerais, Brazil, known for its industrial activity and automotive manufacturing sector.
-
E.
Brasópolis
Brasópolis is a municipality in the state of Minas Gerais, Brazil, known for its mountainous landscapes and proximity to the Mantiqueira mountain range.
- 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_69e0c45e5b8881908ac18fc2f493b114 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee9d0ae0e88190a6042effd93cd455 |
completed | April 26, 2026, 11:17 p.m. |
Created at: April 16, 2026, 6:27 p.m.