Triple

T14737488
Position Surface form Disambiguated ID Type / Status
Subject Manaus Air Base E346251 entity
Predicate location P40 FINISHED
Object Manaus E95648 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: Manaus | Statement: [Manaus Air Base, location, Manaus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manaus
Context triple: [Manaus Air Base, location, Manaus]
  • A. Manaus chosen
    Manaus is a major Brazilian city and capital of the state of Amazonas, known as a key gateway to the Amazon rainforest and an important industrial and cultural center in the region.
  • B. Belém do Pará
    Belém do Pará is a major port city in northern Brazil, known as the gateway to the Amazon region and an important cultural and economic center.
  • C. Belém
    Belém is a historic riverside district of Lisbon, Portugal, known for its monuments of the Age of Discoveries, including the Belém Tower and Jerónimos Monastery.
  • D. Várzea Grande
    Várzea Grande is a city in the Brazilian state of Mato Grosso, located in the central-west region of the country and forming part of the metropolitan area of the state capital, Cuiabá.
  • E. Botucatu
    Botucatu is a municipality in southeastern Brazil known for its higher-education institutions, especially São Paulo State University (UNESP), and its surrounding sandstone cliffs and natural landscapes.
  • 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_69d822e6f1c88190bc494d491a907114 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec73264848190be23c5f0260cbe13 completed April 14, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb90378481909a3083680f11101c completed May 8, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:29 a.m.