Triple

T5309248
Position Surface form Disambiguated ID Type / Status
Subject Ranco Province E118979 entity
Predicate containsCommune P15149 FINISHED
Object Río Bueno E131824 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: Río Bueno | Statement: [Ranco Province, containsCommune, Río Bueno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Río Bueno
Context triple: [Ranco Province, containsCommune, 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. Río Negro
    Río Negro is a major river in Argentine Patagonia known for irrigating fertile valleys and supporting agriculture and settlements across the region.
  • D. Río Negro
    Río Negro is a river in the Cundinamarca Department of central Colombia, contributing to the region’s Andean watershed and local ecosystems.
  • E. El Chañar
    El Chañar is a small rural settlement located in the Río Hurtado area of Chile’s Coquimbo Region.
  • 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_69bd446b57bc8190a513d2e6c40314f3 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd8532c26c819084f5b8de542cd309 completed March 20, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11331275c8190950247127d8e33c6 completed March 23, 2026, 10:17 a.m.
Created at: March 20, 2026, 1:53 p.m.