Triple

T17668079
Position Surface form Disambiguated ID Type / Status
Subject Río Rahue E440439 entity
Predicate mouthOfWatercourse P3817 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: [Río Rahue, mouthOfWatercourse, Río Bueno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Río Bueno
Context triple: [Río Rahue, mouthOfWatercourse, 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_69d8b9e87e18819087104a44dc4dc5b1 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e46f6723d081908eaa57eef6d70bd0 completed April 19, 2026, 6 a.m.
Created at: April 10, 2026, 9:58 a.m.