Triple
T10303316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Região Serrana (Rio de Janeiro) |
E241686
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Macuco
Macuco is a small municipality located in the mountainous Região Serrana of the state of Rio de Janeiro, Brazil.
|
E863577
|
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: Macuco | Statement: [Região Serrana (Rio de Janeiro), hasCity, Macuco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Macuco Context triple: [Região Serrana (Rio de Janeiro), hasCity, Macuco]
-
A.
Itaquaquecetuba
Itaquaquecetuba is a municipality in the Greater São Paulo metropolitan area of southeastern Brazil, known for its rapid urban growth and industrial activity.
-
B.
Itapura
Itapura is a municipality in the state of São Paulo, Brazil, located on the banks of the Tietê River near its confluence with the Paraná River.
-
C.
Catumbi
Catumbi is a traditional neighborhood in Rio de Janeiro, Brazil, known for its central location and historical urban character.
-
D.
Parnamirim
Parnamirim is a rapidly growing city in northeastern Brazil known for its proximity to Natal and its historical role in World War II aviation.
-
E.
Icó
Icó is a historic municipality in northeastern Brazil known for its colonial architecture and cultural heritage within the state of Ceará.
- 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: Macuco Triple: [Região Serrana (Rio de Janeiro), hasCity, Macuco]
Generated description
Macuco is a small municipality located in the mountainous Região Serrana of the state of Rio de Janeiro, Brazil.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Macuco Target entity description: Macuco is a small municipality located in the mountainous Região Serrana of the state of Rio de Janeiro, Brazil.
-
A.
Itaquaquecetuba
Itaquaquecetuba is a municipality in the Greater São Paulo metropolitan area of southeastern Brazil, known for its rapid urban growth and industrial activity.
-
B.
Itapura
Itapura is a municipality in the state of São Paulo, Brazil, located on the banks of the Tietê River near its confluence with the Paraná River.
-
C.
Catumbi
Catumbi is a traditional neighborhood in Rio de Janeiro, Brazil, known for its central location and historical urban character.
-
D.
Parnamirim
Parnamirim is a rapidly growing city in northeastern Brazil known for its proximity to Natal and its historical role in World War II aviation.
-
E.
Icó
Icó is a historic municipality in northeastern Brazil known for its colonial architecture and cultural heritage within the state of Ceará.
- 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d30846108190875042ab1c0204e0 |
completed | April 7, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d87e4cdf8881908d613a0cb65fa0c2 |
completed | April 10, 2026, 4:36 a.m. |
| NEDg | Description generation | batch_69d886c325c4819089dac35eb26e7961 |
completed | April 10, 2026, 5:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d88dbbe97c8190861e08f3ff39f91b |
completed | April 10, 2026, 5:42 a.m. |
Created at: April 6, 2026, 11:45 a.m.