Triple

T10071949
Position Surface form Disambiguated ID Type / Status
Subject Rio Largo E213650 entity
Predicate hasCapitalNearby P33891 FINISHED
Object Maceió E171696 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: Maceió | Statement: [Rio Largo, hasCapitalNearby, Maceió]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maceió
Context triple: [Rio Largo, hasCapitalNearby, Maceió]
  • A. Maceió chosen
    Maceió is a coastal city in northeastern Brazil known for its white-sand beaches, turquoise waters, and vibrant tourism industry.
  • B. Aracaju
    Aracaju is a coastal city in northeastern Brazil known for its planned urban layout, beaches, and role as an administrative and economic center.
  • 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. 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.
  • E. Jaboatão dos Guararapes
    Jaboatão dos Guararapes is a major coastal city in northeastern Brazil known for its historical significance in the Dutch-Portuguese conflicts and its integration into the metropolitan area of Recife.
  • 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_69ca839add308190b57d53b4ec21f2d0 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd01279388190b94c8def00425c78 completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2cbc0388c8190bc10d462068c9e38 completed April 5, 2026, 8:53 p.m.
Created at: March 30, 2026, 8:59 p.m.