Triple

T12727213
Position Surface form Disambiguated ID Type / Status
Subject Port of Salvador E304137 entity
Predicate locatedIn P40 FINISHED
Object Salvador, Bahia E62572 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: Salvador, Bahia | Statement: [Port of Salvador, locatedIn, Salvador, Bahia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Salvador, Bahia
Context triple: [Port of Salvador, locatedIn, Salvador, Bahia]
  • A. Salvador, Bahia, Brazil chosen
    Salvador, the capital of Brazil’s Bahia state, is a major coastal city known for its Afro-Brazilian culture, colonial architecture, and historic role as the country’s first capital.
  • B. Feira de Santana
    Feira de Santana is a major commercial and transportation hub in northeastern Brazil and the second-largest city in the state of Bahia.
  • C. Recife
    Recife is a major coastal city in northeastern Brazil known for its historic colonial architecture, extensive waterways, and role as an important cultural and economic center.
  • D. Aracaju
    Aracaju is a coastal city in northeastern Brazil known for its planned urban layout, beaches, and role as an administrative and economic center.
  • E. Belém do Pará
    Belém do Pará is a major port city in northern Brazil, known as the gateway to the Amazon region and an important cultural and economic 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96415ebe48190ae935bc3a9b00f65 completed April 10, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6f5b9e0c4819095194dc42677e17f completed May 3, 2026, 7:14 a.m.
Created at: April 9, 2026, 5:25 p.m.