Triple
T16416105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nor Yungas Province |
E398688
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Caranavi |
E296350
|
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: Caranavi | Statement: [Nor Yungas Province, hasSettlement, Caranavi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caranavi Context triple: [Nor Yungas Province, hasSettlement, Caranavi]
-
A.
Caranavi
chosen
Caranavi is a Bolivian town known as a key coffee-growing and agricultural hub in the Yungas region.
-
B.
Naguanagua
Naguanagua is a suburban municipality and city in the state of Carabobo, Venezuela, known for its residential areas, commercial centers, and proximity to the regional capital Valencia.
-
C.
Lumbaquí
Lumbaquí is a small town in northeastern Ecuador that serves as a local hub within the Amazonian Sucumbíos Province.
-
D.
Guayaramerín
Guayaramerín is a Bolivian town and river port in the Beni Department, located on the Mamoré River near the border with Brazil.
-
E.
Guará
Guará is an administrative region and residential suburb within Brazil’s Federal District, located near Brasília.
- 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_69d87f2b9024819085c20e52de95d583 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32877ff248190886717d3329421a7 |
completed | April 18, 2026, 6:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f457b8c8190b278697ef43301cb |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:09 a.m.