Triple

T23276109
Position Surface form Disambiguated ID Type / Status
Subject Metropolitan Region of Fortaleza E588722 entity
Predicate hasMunicipality P847 FINISHED
Object Maracanaú 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: Maracanaú | Statement: [Metropolitan Region of Fortaleza, hasMunicipality, Maracanaú]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maracanaú
Context triple: [Metropolitan Region of Fortaleza, hasMunicipality, Maracanaú]
  • A. Maracanaú chosen
    Maracanaú is an industrial and residential city in northeastern Brazil, located in the metropolitan region of Fortaleza in the state of Ceará.
  • B. Vitória de Santo Antão
    Vitória de Santo Antão is a municipality in northeastern Brazil known for its sugarcane-based economy, cachaça production, and colonial-era heritage.
  • C. Macaíba
    Macaíba is a municipality in the state of Rio Grande do Norte, Brazil, known for its historical significance and integration into the greater Natal urban area.
  • D. Cumbuco
    Cumbuco is a coastal village in northeastern Brazil known for its sand dunes, lagoons, and strong winds that make it a popular destination for kitesurfing and other beach tourism.
  • E. Parnamirim
    Parnamirim is a rapidly growing city in northeastern Brazil known for its proximity to Natal and its historical role in World War II aviation.
  • 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_69e25d16e2c08190a291de254703129e completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f19577841481909acc17bb565bae5c completed April 29, 2026, 5:21 a.m.
Created at: April 17, 2026, 4:48 p.m.