Triple

T10064006
Position Surface form Disambiguated ID Type / Status
Subject Arena da Amazônia E213054 entity
Predicate locatedIn P40 FINISHED
Object Amazonas E367132 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: Amazonas | Statement: [Arena da Amazônia, locatedIn, Amazonas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amazonas
Context triple: [Arena da Amazônia, locatedIn, Amazonas]
  • A. 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.
  • B. Amaszonas
    Amaszonas is a Bolivian regional airline that operates domestic and short-haul international flights across South America.
  • C. 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.
  • D. Rio Negro
    Rio Negro is a major blackwater river in South America that flows through Colombia, Venezuela, and Brazil before joining the Amazon River.
  • E. Orinoco River
    The Orinoco River is one of the longest and most important rivers in South America, flowing through Venezuela and Colombia and supporting vast tropical ecosystems and human settlements.
  • 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_69ca83977128819084084eb7d1d8c52a completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdcfd653748190aeddf7a679028604 completed April 2, 2026, 2:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29a7bd56c8190a6c43df26db880f4 completed April 5, 2026, 5:23 p.m.
Created at: March 30, 2026, 8:58 p.m.