Triple
T21896813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Los Ríos Region |
E540699
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Río Bueno |
—
|
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: Río Bueno | Statement: [Los Ríos Region, hasCity, Río Bueno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Río Bueno Context triple: [Los Ríos Region, hasCity, Río Bueno]
-
A.
Río Bueno
chosen
Río Bueno is a Chilean city known for its agricultural surroundings and location along the Bueno River in the Los Ríos Region.
-
B.
Río Hurtado
Río Hurtado is a rural Chilean municipality and valley area in the Coquimbo Region, known for its Andean landscapes, agriculture, and archaeological sites.
-
C.
Ríos Rosas
Ríos Rosas is a Madrid Metro station located in the Chamberí district, serving as part of the city's historic Line 1.
-
D.
Río Limay
Río Limay is a major river in Argentine Patagonia, known for its clear waters, hydroelectric dams, and role in forming the Limay Valley and several large reservoirs.
-
E.
Río Negro
Río Negro is a major river in Argentine Patagonia known for irrigating fertile valleys and supporting agriculture and settlements across the region.
- 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_69e0c47a95908190ae3e19b716accb3d |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f11fc700c08190a470fe1ad76c8509 |
completed | April 28, 2026, 8:59 p.m. |
Created at: April 16, 2026, 7:07 p.m.