Triple

T22642699
Position Surface form Disambiguated ID Type / Status
Subject Recife City Hall E558872 entity
Predicate locatedIn P40 FINISHED
Object Recife NE NERFINISHED

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: Recife | Statement: [Recife City Hall, locatedIn, Recife]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Recife
Context triple: [Recife City Hall, locatedIn, Recife]
  • A. Recife chosen
    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.
  • 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. 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.
  • D. Maceió
    Maceió is a coastal city in northeastern Brazil known for its white-sand beaches, turquoise waters, and vibrant tourism industry.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e24547f7fc819086e2c4ba3b979657 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1703489a48190bd97a7eb7a571b64 completed April 29, 2026, 2:43 a.m.
Created at: April 17, 2026, 3:04 p.m.