Triple

T3533991
Position Surface form Disambiguated ID Type / Status
Subject Tomé de Sousa E74725 entity
Predicate founded P104 FINISHED
Object Salvador da 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 da Bahia | Statement: [Tomé de Sousa, founded, Salvador da Bahia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Salvador da Bahia
Context triple: [Tomé de Sousa, founded, Salvador da 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. Bahia
    Bahia is a traditional Brazilian football club based in Salvador, known for its passionate fanbase and historic success in national competitions.
  • C. Bahia
    Bahia is a large and culturally rich state in northeastern Brazil, known for its Afro-Brazilian heritage, historic city of Salvador, and extensive Atlantic coastline.
  • D. 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.
  • E. São Luís
    São Luís is the historic capital of the Brazilian state of Maranhão, known for its well-preserved colonial architecture and rich Afro-Brazilian cultural heritage.
  • 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_69ad85d1a3948190931fd1ea1f49717b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbc9cff5c81909011f34c9bf28e11 completed March 8, 2026, 6:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e9c408481909a808d400f545ff8 completed March 13, 2026, 3:03 a.m.
Created at: March 8, 2026, 3:19 p.m.