Triple

T11911896
Position Surface form Disambiguated ID Type / Status
Subject AZU E283415 entity
Predicate airlineSecondaryHubCountry P12358 FINISHED
Object Brazil E19289 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: Brazil | Statement: [AZU, airlineSecondaryHubCountry, Brazil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brazil
Context triple: [AZU, airlineSecondaryHubCountry, Brazil]
  • A. Brazil chosen
    Brazil is the largest country in South America, known for its vast Amazon rainforest, diverse culture, and major cities like São Paulo and Rio de Janeiro.
  • B. Brazil
    Brazil is a 1985 dystopian science fiction film known for its darkly satirical portrayal of a bureaucratic, totalitarian society and its distinctive, surreal visual style.
  • C. Brasyl
    Brasyl is a science fiction novel by Ian McDonald that intertwines multiple timelines in Brazil to explore themes of quantum reality, culture, and globalization.
  • D. Portela
    Portela is a residential parish in the municipality of Loures, within the Lisbon metropolitan area of Portugal.
  • E. Republic of the United States of Brazil
    The Republic of the United States of Brazil was the federal republican regime that succeeded the Brazilian monarchy in 1889 and governed Brazil through much of the 20th century.
  • 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: airlineSecondaryHubCountry
Context triple: [AZU, airlineSecondaryHubCountry, Brazil]
  • A. secondaryHubOfAirline
    Indicates that an airport serves as a secondary operational hub for a particular airline, supporting but not replacing its primary hub activities.
  • B. linkedAirlineCountry chosen
    Indicates that there is an association between an airline and a country, such as the country where the airline is based, registered, or primarily operates.
  • C. hasSecondaryAirport
    Indicates that an entity is associated with an additional, typically smaller or alternative, airport beyond its primary one.
  • D. operatorSecondaryHubAirportIATA
    Indicates the IATA airport code of a secondary hub airport used by the operator.
  • E. associatedAirportCountrySubdivision
    Indicates the specific country subdivision (such as a state, province, or region) in which the associated airport is located.
  • 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_69d6ab2c07e88190ba13b0d21fd6cf33 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8e528f6748190ac873a040a61fa93 completed April 10, 2026, 11:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69f43fe43c7c8190a85d464fd48e00d9 completed May 1, 2026, 5:53 a.m.
PD Predicate disambiguation batch_69d8bb3632ac8190b13e53c2b5db7125 completed April 10, 2026, 8:56 a.m.
Created at: April 8, 2026, 9:44 p.m.