Triple

T16325889
Position Surface form Disambiguated ID Type / Status
Subject Sé, São Paulo E396416 entity
Predicate hasPart P35 FINISHED
Object Vale do Anhangabaú E953551 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: Vale do Anhangabaú | Statement: [Sé, São Paulo, hasPart, Vale do Anhangabaú]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vale do Anhangabaú
Context triple: [Sé, São Paulo, hasPart, Vale do Anhangabaú]
  • A. Campo de Congonhas
    Campo de Congonhas is the historic airfield area in São Paulo, Brazil, that gave rise to and lends its name to the modern Congonhas–São Paulo Airport.
  • B. Pirajá
    Pirajá is a neighborhood in Salvador, Bahia, Brazil, historically notable as a key site in Brazil’s struggle for independence.
  • C. Ilha do Retiro
    Ilha do Retiro is a football stadium in Recife, Brazil, best known as the home ground of Sport Club do Recife.
  • D. Poço das Antas
    Poço das Antas is a small municipality in the Vale do Taquari region of Rio Grande do Sul, Brazil, known for its rural landscape and agricultural activities.
  • E. Largo São Bento chosen
    Largo São Bento is a traditional square in downtown São Paulo known for its historic Benedictine monastery and its role as a cultural and religious landmark in the city’s historic center.
  • 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_69d87f255b788190a400eba031dd85d8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e296b9dcb88190beb0ca2206729175 completed April 17, 2026, 8:23 p.m.
NED1 Entity disambiguation (via context triple) batch_6a002da915ac8190820acbe0db72c8a1 completed May 10, 2026, 7:03 a.m.
Created at: April 10, 2026, 5:06 a.m.