Triple
T10543398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Região Sul Fluminense |
E248752
|
entity |
| Predicate | majorCity |
P316
|
FINISHED |
| Object | Volta Redonda |
E250440
|
NE FINISHED |
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: Volta Redonda | Statement: [Região Sul Fluminense, majorCity, Volta Redonda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Volta Redonda Context triple: [Região Sul Fluminense, majorCity, Volta Redonda]
-
A.
Volta Redonda
chosen
Volta Redonda is an industrial city in southeastern Brazil best known for its major steel production complex and role in the country’s metallurgical sector.
-
B.
Resende
Resende is a Portuguese municipality in the Douro region, known for its scenic river landscapes and production of cherries and vinho verde.
-
C.
Três Rios
Três Rios is a municipality in the state of Rio de Janeiro, Brazil, known as a regional commercial and logistical hub at the confluence of three rivers.
-
D.
Teresópolis
Teresópolis is a mountainous city in the state of Rio de Janeiro, Brazil, known for its cool climate, natural parks, and role as a popular ecotourism and weekend getaway destination.
-
E.
Macaé
Macaé is a coastal city in southeastern Brazil known for its offshore oil industry and role as a major hub for petroleum exploration.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d51911b10481909e6e548879e8de36 |
completed | April 7, 2026, 2:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69de22087d008190a9db6080b8c10f5d |
completed | April 14, 2026, 11:16 a.m. |
Created at: April 6, 2026, 12:32 p.m.