Triple

T5976534
Position Surface form Disambiguated ID Type / Status
Subject Ilha do Zeca (Afogados) E133011 entity
Predicate locatedIn P40 FINISHED
Object Afogados E137924 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: Afogados | Statement: [Ilha do Zeca (Afogados), locatedIn, Afogados]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Afogados
Context triple: [Ilha do Zeca (Afogados), locatedIn, Afogados]
  • A. Afogados chosen
    Afogados is a populous neighborhood in the Brazilian city of Recife, known for its busy commercial areas and dense urban character.
  • B. Catumbi
    Catumbi is a traditional neighborhood in Rio de Janeiro, Brazil, known for its central location and historical urban character.
  • C. Ourinhos
    Ourinhos is a municipality in the southwestern part of the state of São Paulo, Brazil, known as a regional commercial and agricultural center.
  • D. Parnamirim
    Parnamirim is a rapidly growing city in northeastern Brazil known for its proximity to Natal and its historical role in World War II aviation.
  • E. Caieiras
    Caieiras is a municipality in the metropolitan region of São Paulo, Brazil, known for its industrial activity and surrounding green areas.
  • 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_69c0086f45e8819098f73dd16d45ec9d completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04a3b41248190b259409f8ebb9e09 completed March 22, 2026, 7:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69c10847cdec81908a4d2d19d8a53d1d completed March 23, 2026, 9:30 a.m.
Created at: March 22, 2026, 4:04 p.m.