Triple
T11831239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lajeado |
E281396
|
entity |
| Predicate | state |
P87
|
FINISHED |
| Object | Rio Grande do Sul |
E208924
|
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: Rio Grande do Sul | Statement: [Lajeado, state, Rio Grande do Sul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rio Grande do Sul Context triple: [Lajeado, state, Rio Grande do Sul]
-
A.
Rio Grande do Sul
chosen
Rio Grande do Sul is Brazil’s southernmost state, known for its gaucho culture, strong agricultural economy, and shared borders with Uruguay and Argentina.
-
B.
Mato Grosso do Sul
Mato Grosso do Sul is a landlocked state in Brazil’s Center-West region, known for its vast Pantanal wetlands, rich biodiversity, and cattle ranching economy.
-
C.
Paraná state
Paraná state is a southern Brazilian state known for its diverse landscapes, major agricultural production, and popular natural attractions including part of the Iguaçu National Park.
-
D.
Santa Catarina
Santa Catarina is an industrial and residential city in the Monterrey metropolitan area of the Mexican state of Nuevo León.
-
E.
Santa Catarina
Santa Catarina is a southern Brazilian state known for its strong German cultural heritage, picturesque coastal and mountainous landscapes, and significant industrial and agricultural economy.
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a62c95988190a45dbaa7001c8846 |
completed | April 10, 2026, 7:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6b8b788308190bd9c3b68569bc56a |
completed | May 3, 2026, 2:53 a.m. |
Created at: April 8, 2026, 9:43 p.m.