Triple
T19221094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acre (state) |
E480613
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Rio Branco |
—
|
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: Rio Branco | Statement: [Acre (state), capital, Rio Branco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rio Branco Context triple: [Acre (state), capital, Rio Branco]
-
A.
Rio Branco
chosen
Rio Branco is the capital city of the Brazilian state of Acre, located in the western Amazon region.
-
B.
Rio Branco
Rio Branco is a major river in northern Brazil that flows through the state of Roraima and ultimately joins the Rio Negro in the Amazon basin.
-
C.
Ji-Paraná
Ji-Paraná is a major municipality and economic center located in the Brazilian state of Rondônia in the western Amazon region.
-
D.
Kungur
Kungur is a historic Russian town in Perm Krai known for its ice cave, traditional trade heritage, and role as a regional cultural center.
-
E.
Corumbá
Corumbá is a Brazilian city in the state of Mato Grosso do Sul, known as a key gateway to the Pantanal wetlands and an important regional center for river trade and ecotourism.
- 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_69d8e8cb8c348190b52075823911c869 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fa3fa9348190920f9d41b8beb900 |
completed | April 20, 2026, 10:04 a.m. |
Created at: April 10, 2026, 1:24 p.m.