Triple
T10303310
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Região Serrana (Rio de Janeiro) |
E241686
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Nova Friburgo |
E558929
|
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: Nova Friburgo | Statement: [Região Serrana (Rio de Janeiro), hasCity, Nova Friburgo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nova Friburgo Context triple: [Região Serrana (Rio de Janeiro), hasCity, Nova Friburgo]
-
A.
Nova Friburgo
chosen
Nova Friburgo is a mountainous city in the state of Rio de Janeiro, Brazil, known for its Swiss-influenced architecture, cool climate, and textile industry.
-
B.
Canoas
Canoas is a major industrial and residential city in the Porto Alegre metropolitan region of Rio Grande do Sul, Brazil.
-
C.
Novo Hamburgo
Novo Hamburgo is a city in southern Brazil known for its strong German immigrant heritage and influential role in the country’s footwear industry.
-
D.
Volta Redonda
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.
-
E.
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.
- 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_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_69d71d4f6c30819098bcdc77ba1836c3 |
completed | April 9, 2026, 3:30 a.m. |
Created at: April 6, 2026, 11:45 a.m.