Triple
T19404159
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guajará-Mirim |
E485405
|
entity |
| Predicate | distanceTo |
P350
|
FINISHED |
| Object | Porto Velho, Rondônia |
—
|
NE NERFINISHED |
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: Porto Velho, Rondônia | Statement: [Guajará-Mirim, distanceTo, Porto Velho, Rondônia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Porto Velho, Rondônia Context triple: [Guajará-Mirim, distanceTo, Porto Velho, Rondônia]
-
A.
Porto Velho
chosen
Porto Velho is the capital and largest city of the Brazilian state of Rondônia, located in the western Amazon region.
-
B.
Dourados
Dourados is a major agricultural and commercial city in the Brazilian state of Mato Grosso do Sul, known as an important regional economic and educational center.
-
C.
Goiânia
Goiânia is the capital and largest city of the Brazilian state of Goiás, known as a major regional center for agriculture, industry, and services in central Brazil.
-
D.
Belém do Pará
Belém do Pará is a major port city in northern Brazil, known as the gateway to the Amazon region and an important cultural and economic center.
-
E.
Ariquemes
Ariquemes is a municipality and important regional center in the Brazilian state of Rondônia, known for agriculture, cattle ranching, and its role in Amazonian frontier development.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d5162481909db12435d9535c1a |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6257937d081909dbc5804d2505938 |
completed | April 20, 2026, 1:09 p.m. |
Created at: April 10, 2026, 1:36 p.m.