Triple

T19733716
Position Surface form Disambiguated ID Type / Status
Subject Maestro Wilson Fonseca International Airport E473919 entity
Predicate alternativeName P39 FINISHED
Object Santarém–Maestro Wilson Fonseca International Airport NE NERFINISHED

How this triple was built (3 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: Santarém–Maestro Wilson Fonseca International Airport | Statement: [Maestro Wilson Fonseca International Airport, alternativeName, Santarém–Maestro Wilson Fonseca International Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Santarém–Maestro Wilson Fonseca International Airport
Context triple: [Maestro Wilson Fonseca International Airport, alternativeName, Santarém–Maestro Wilson Fonseca International Airport]
  • A. São Luís International Airport
    São Luís International Airport is the main commercial airport serving the city of São Luís in the Brazilian state of Maranhão, handling domestic and limited international flights.
  • B. Francisco Sá Carneiro Airport
    Francisco Sá Carneiro Airport is the main international airport serving Porto, Portugal, and one of the country’s busiest air transport hubs.
  • C. São Jorge Airport
    São Jorge Airport is a small regional airport in the Azores archipelago of Portugal that provides air connections between São Jorge Island and other islands and mainland destinations.
  • D. Macapá International Airport
    Macapá International Airport is the main commercial aviation hub serving the city of Macapá and the surrounding region in Brazil’s northern Amazon area.
  • E. Eduardo Gomes International Airport
    Eduardo Gomes International Airport is the main international airport serving Manaus in Brazil’s Amazonas state, handling both passenger traffic and significant cargo operations in the Amazon region.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Santarém–Maestro Wilson Fonseca International Airport
Target entity description: Santarém–Maestro Wilson Fonseca International Airport is a Brazilian airport serving the city of Santarém in the state of Pará, providing regional and limited international air connections in the Amazon region.
  • A. São Luís International Airport
    São Luís International Airport is the main commercial airport serving the city of São Luís in the Brazilian state of Maranhão, handling domestic and limited international flights.
  • B. Francisco Sá Carneiro Airport
    Francisco Sá Carneiro Airport is the main international airport serving Porto, Portugal, and one of the country’s busiest air transport hubs.
  • C. São Jorge Airport
    São Jorge Airport is a small regional airport in the Azores archipelago of Portugal that provides air connections between São Jorge Island and other islands and mainland destinations.
  • D. Macapá International Airport
    Macapá International Airport is the main commercial aviation hub serving the city of Macapá and the surrounding region in Brazil’s northern Amazon area.
  • E. Eduardo Gomes International Airport
    Eduardo Gomes International Airport is the main international airport serving Manaus in Brazil’s Amazonas state, handling both passenger traffic and significant cargo operations in the Amazon region.
  • F. None of above. chosen

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_69d8e517ebd48190979ee76723bcfadf completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6515b4d308190af3be1787fa7c65b completed April 20, 2026, 4:16 p.m.
Created at: April 10, 2026, 1:47 p.m.