Triple

T1419334
Position Surface form Disambiguated ID Type / Status
Subject GOL Linhas Aéreas Inteligentes E31987 entity
Predicate headquartersLocation P62 FINISHED
Object São Paulo E9033 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: São Paulo | Statement: [GOL Linhas Aéreas Inteligentes, headquartersLocation, São Paulo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: São Paulo
Context triple: [GOL Linhas Aéreas Inteligentes, headquartersLocation, São Paulo]
  • A. São Paulo chosen
    São Paulo is Brazil’s largest city and a major global financial, cultural, and industrial center in South America.
  • B. Belo Horizonte
    Belo Horizonte is the capital and largest city of the Brazilian state of Minas Gerais, known for its modernist architecture, surrounding mountains, and vibrant cultural and economic life.
  • C. Rio de Janeiro
    Rio de Janeiro is a major Brazilian coastal city famed for its stunning beaches, dramatic landscape, Carnival festival, and iconic Christ the Redeemer statue.
  • D. Campinas
    Campinas is a major city in the state of São Paulo, Brazil, known as an important industrial, technological, and transportation hub in the country.
  • E. Curitiba
    Curitiba is the capital and largest city of the Brazilian state of Paraná, known for its innovative urban planning, extensive public transportation system, and high quality of life.
  • 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_69a49919a994819086528951bc224775 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c40631e881909ddf81a2eb84af1c completed March 1, 2026, 10:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad293cb8f0819085bea7914abf0683 completed March 8, 2026, 7:46 a.m.
Created at: March 1, 2026, 7:59 p.m.