Triple

T7019508
Position Surface form Disambiguated ID Type / Status
Subject G3 E162782 entity
Predicate operatorPrimaryHubAirport P8171 FINISHED
Object São Paulo/Guarulhos–Governador André Franco Montoro International Airport E59690 NE FINISHED

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: São Paulo/Guarulhos–Governador André Franco Montoro International Airport | Statement: [G3, operatorPrimaryHubAirport, São Paulo/Guarulhos–Governador André Franco Montoro International Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: São Paulo/Guarulhos–Governador André Franco Montoro International Airport
Context triple: [G3, operatorPrimaryHubAirport, São Paulo/Guarulhos–Governador André Franco Montoro International Airport]
  • A. São Paulo–Guarulhos International Airport chosen
    São Paulo–Guarulhos International Airport is Brazil’s busiest and largest international airport, serving as a major hub for domestic and international flights in the São Paulo metropolitan area.
  • B. Campinas-Viracopos International Airport
    Campinas-Viracopos International Airport is a major Brazilian airport in the state of São Paulo, known for its significant cargo operations and growing role as a passenger hub.
  • C. Congonhas–São Paulo Airport
    Congonhas–São Paulo Airport is one of São Paulo’s main domestic airports, known for its central urban location and heavy business travel traffic.
  • D. Presidente Juscelino Airport
    Presidente Juscelino Airport is a Brazilian airport named in honor of former president Juscelino Kubitschek, reflecting his historical significance to the country.
  • E. Curitiba-Afonso Pena International Airport
    Curitiba-Afonso Pena International Airport is a major airport in southern Brazil serving the city of Curitiba and acting as an important regional hub for domestic and international flights.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: operatorPrimaryHubAirport
Context triple: [G3, operatorPrimaryHubAirport, São Paulo/Guarulhos–Governador André Franco Montoro International Airport]
  • A. hubAirport chosen
    Indicates that an airport serves as a primary hub or central operating base for a particular airline or carrier.
  • B. airportServesAs
    Indicates that an airport functions in a particular role or capacity (such as primary, secondary, or hub) for a specified area, organization, or service.
  • C. airportServed
    Indicates that a particular airport provides service to, or is used for air travel to and from, a given location or area.
  • D. airportUse
    Indicates that an airport is used or utilized by a particular entity, such as an airline, organization, or service.
  • E. airportStation
    Indicates a location functions as an airport facility where air transport operations occur.
  • F. None of above.

Provenance (4 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_69c6885b26248190a857541e3d10e299 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6e5ecd4488190bf19e42de55da98b completed March 27, 2026, 8:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c775707e30819088b311a1a87eee79 completed March 28, 2026, 6:30 a.m.
PD Predicate disambiguation batch_69c6e1b8118481909d76eb6616160e80 completed March 27, 2026, 7:59 p.m.
Created at: March 27, 2026, 2:34 p.m.