Triple

T11795854
Position Surface form Disambiguated ID Type / Status
Subject Vale do Itajaí E280503 entity
Predicate hasMajorCity P316 FINISHED
Object Itajaí E287768 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: Itajaí | Statement: [Vale do Itajaí, hasMajorCity, Itajaí]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Itajaí
Context triple: [Vale do Itajaí, hasMajorCity, Itajaí]
  • A. Itajaí chosen
    Itajaí is a coastal city in the Brazilian state of Santa Catarina known for its strong German-Brazilian cultural heritage and important Atlantic port.
  • B. Brusque
    Brusque is a city in the Brazilian state of Santa Catarina known for its strong German-Brazilian heritage and textile industry.
  • C. Florianópolis
    Florianópolis is the capital city of the Brazilian state of Santa Catarina, known for its numerous beaches, tourism, and high quality of life.
  • D. Itanhaém
    Itanhaém is a coastal municipality in southeastern Brazil known for its beaches, historic colonial center, and tourism along the São Paulo state shoreline.
  • E. Jaraguá do Sul
    Jaraguá do Sul is a city in southern Brazil known for its strong German-Brazilian cultural heritage and industrial economy.
  • 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5a1cda0819092d66a82fd882786 completed April 10, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69f43f8a57ec8190aded70ae89aa8cf7 completed May 1, 2026, 5:52 a.m.
Created at: April 8, 2026, 9:42 p.m.