Triple

T19303189
Position Surface form Disambiguated ID Type / Status
Subject Santa Isabel do Rio Negro E482752 entity
Predicate isMunicipalityOf P852 FINISHED
Object Amazonas 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: Amazonas | Statement: [Santa Isabel do Rio Negro, isMunicipalityOf, Amazonas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amazonas
Context triple: [Santa Isabel do Rio Negro, isMunicipalityOf, Amazonas]
  • A. Amazonas
    Amazonas is a vast, sparsely populated state in southern Venezuela known for its dense Amazon rainforest, indigenous communities, and rich biodiversity.
  • B. Amazonas chosen
    Amazonas is a vast state in northwestern Brazil, largely covered by the Amazon rainforest and known for its immense biodiversity and the city of Manaus.
  • C. Amazonas
    Amazonas is a vast, sparsely populated department in southern Colombia known for its dense Amazon rainforest, rich biodiversity, and access to the Amazon River.
  • D. Amaszonas
    Amaszonas is a Bolivian regional airline that operates domestic and short-haul international flights across South America.
  • E. Amazon River
    The Amazon River is one of the world's longest and largest rivers by discharge, flowing across northern South America through the Amazon rainforest and into the Atlantic Ocean.
  • 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_69d8e8d04d5c8190baa816986f2b1d1e completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e604c5903c819090b3f89c3f33b005 completed April 20, 2026, 10:49 a.m.
Created at: April 10, 2026, 1:31 p.m.