Triple

T5976112
Position Surface form Disambiguated ID Type / Status
Subject Guabiraba E132996 entity
Predicate locatedInRegion P40 FINISHED
Object Norte do Recife E135136 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: Norte do Recife | Statement: [Guabiraba, locatedInRegion, Norte do Recife]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norte do Recife
Context triple: [Guabiraba, locatedInRegion, Norte do Recife]
  • A. Limoeiro do Norte
    Limoeiro do Norte is a municipality in northeastern Brazil known for its agricultural production and location in the state of Ceará.
  • B. Petrolina
    Petrolina is a major city in northeastern Brazil known for its irrigated fruit production and location along the São Francisco River.
  • C. 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.
  • D. 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.
  • E. Boa Viagem chosen
    Boa Viagem is a famous beachfront neighborhood in Recife, Brazil, known for its long urban beach, high-rise skyline, and vibrant tourist scene.
  • 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_69c0086f45e8819098f73dd16d45ec9d completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04a3b41248190b259409f8ebb9e09 completed March 22, 2026, 7:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e4184a708190a9e4fe8453463a4b completed March 23, 2026, 6:56 a.m.
Created at: March 22, 2026, 4:04 p.m.