Triple
T10058590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rio Grande do Sul |
E208924
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Pelotas |
E656524
|
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: Pelotas | Statement: [Rio Grande do Sul, contains, Pelotas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pelotas Context triple: [Rio Grande do Sul, contains, Pelotas]
-
A.
Pelotas
chosen
Pelotas is a historic city in southern Brazil known for its colonial architecture, cultural festivals, and traditional sweets industry.
-
B.
Jaraguá do Sul
Jaraguá do Sul is a city in southern Brazil known for its strong German-Brazilian cultural heritage and industrial economy.
-
C.
Canoas
Canoas is a major industrial and residential city in the Porto Alegre metropolitan region of Rio Grande do Sul, Brazil.
-
D.
Porto Alegre
Porto Alegre is the capital and largest city of Brazil’s southernmost state, Rio Grande do Sul, known for its cultural diversity, strong gaucho traditions, and important role as a regional economic and political center.
-
E.
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.
- 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_69ca836094408190a36a1ea7e9a86fcd |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcfb0f17c8190a8c0cfb02863537d |
completed | April 2, 2026, 2:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d30041f8a88190b24de139e4acf9bb |
completed | April 6, 2026, 12:37 a.m. |
Created at: March 30, 2026, 8:57 p.m.