Triple

T17680997
Position Surface form Disambiguated ID Type / Status
Subject Municipal Market Adolpho Lisboa E440767 entity
Predicate locatedIn P40 FINISHED
Object Manaus 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: Manaus | Statement: [Municipal Market Adolpho Lisboa, locatedIn, Manaus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manaus
Context triple: [Municipal Market Adolpho Lisboa, locatedIn, 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 (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_69d8b9e940b081908b862bb0e6e89b0d completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e470445b3881908bb0930b986089f7 completed April 19, 2026, 6:03 a.m.
Created at: April 10, 2026, 10:01 a.m.