Triple
T13528672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brasópolis |
E323076
|
entity |
| Predicate | officialName |
P66
|
FINISHED |
| Object |
Brasópolis
Brasópolis is a municipality in the state of Minas Gerais, Brazil, known for its mountainous landscapes and proximity to the Mantiqueira mountain range.
|
E1044668
|
NE FINISHED |
How this triple was built (4 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: Brasópolis | Statement: [Brasópolis, officialName, Brasópolis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brasópolis Context triple: [Brasópolis, officialName, Brasópolis]
-
A.
Ribeirópolis
Ribeirópolis is a municipality in the Brazilian state of Sergipe, located in the semi-arid Sertão region and known for its agricultural activities and small-town character.
-
B.
Morrinhos
Morrinhos is a municipality in the Brazilian state of Goiás, known for its agricultural economy and regional thermal springs.
-
C.
Duas Barras
Duas Barras is a small municipality in the mountainous interior of Rio de Janeiro state in southeastern Brazil.
-
D.
Mourão
Mourão is a small municipality in Portugal’s Alentejo region, known for its historic castle and proximity to the Alqueva Reservoir.
-
E.
Bragança Paulista
Bragança Paulista is a municipality in southeastern Brazil known for its historical architecture, mild climate, and role as a regional commercial and educational center.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Brasópolis Triple: [Brasópolis, officialName, Brasópolis]
Generated description
Brasópolis is a municipality in the state of Minas Gerais, Brazil, known for its mountainous landscapes and proximity to the Mantiqueira mountain range.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brasópolis Target entity description: Brasópolis is a municipality in the state of Minas Gerais, Brazil, known for its mountainous landscapes and proximity to the Mantiqueira mountain range.
-
A.
Ribeirópolis
Ribeirópolis is a municipality in the Brazilian state of Sergipe, located in the semi-arid Sertão region and known for its agricultural activities and small-town character.
-
B.
Morrinhos
Morrinhos is a municipality in the Brazilian state of Goiás, known for its agricultural economy and regional thermal springs.
-
C.
Duas Barras
Duas Barras is a small municipality in the mountainous interior of Rio de Janeiro state in southeastern Brazil.
-
D.
Mourão
Mourão is a small municipality in Portugal’s Alentejo region, known for its historic castle and proximity to the Alqueva Reservoir.
-
E.
Bragança Paulista
Bragança Paulista is a municipality in southeastern Brazil known for its historical architecture, mild climate, and role as a regional commercial and educational center.
- F. None of above. chosen
Provenance (5 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafb8e0cc8190b47f6aeb8ced470e |
completed | April 12, 2026, 2:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7549dda6481908e9305690488b1af |
completed | May 3, 2026, 1:58 p.m. |
| NEDg | Description generation | batch_69f7555173d08190be887e81c148192e |
completed | May 3, 2026, 2:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f75675df788190b4aa562fe0bc1d75 |
completed | May 3, 2026, 2:06 p.m. |
Created at: April 9, 2026, 9:44 p.m.