Triple

T4435898
Position Surface form Disambiguated ID Type / Status
Subject Manaus E95648 entity
Predicate state P87 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: [Manaus, state, Amazonas]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amazonas
Context triple: [Manaus, state, 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. 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.
  • C. Rio Negro
    Rio Negro is a major blackwater river in South America that flows through Colombia, Venezuela, and Brazil before joining the Amazon River.
  • D. 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.
  • E. Paraná River
    The Paraná River is one of South America's longest and most important rivers, flowing through Brazil, Paraguay, and Argentina and serving as a key waterway for transport, hydroelectric power, and regional ecosystems.
  • 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_69b3453ea2b48190a26f154b3b8fece5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35589f8608190b0820d36beaacf44 completed March 13, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6375d0d8c819095a27cdc84af9faf completed March 15, 2026, 4:36 a.m.
Created at: March 12, 2026, 11:31 p.m.