Triple

T21940551
Position Surface form Disambiguated ID Type / Status
Subject Ponta Negra neighborhood E541807 entity
Predicate hasPart P35 FINISHED
Object Ponta Negra Beach 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: Ponta Negra Beach | Statement: [Ponta Negra neighborhood, hasPart, Ponta Negra Beach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ponta Negra Beach
Context triple: [Ponta Negra neighborhood, hasPart, Ponta Negra Beach]
  • A. Ponta Negra Beach chosen
    Ponta Negra Beach is a popular urban beach in Natal, Brazil, known for its lively tourist scene and the iconic Morro do Careca sand dune.
  • B. Porto da Barra Beach
    Porto da Barra Beach is a popular urban beach in Salvador, Brazil, known for its calm waters, historic surroundings, and vibrant sunset views.
  • C. Tambaú Beach
    Tambaú Beach is a popular urban beach in João Pessoa, Brazil, known for its calm waters, lively promenade, and proximity to the easternmost point of the Americas.
  • D. Candeias Beach
    Candeias Beach is a popular urban beach in the coastal city of Jaboatão dos Guararapes in Pernambuco, Brazil, known for its calm waters and residential seafront.
  • E. Cumbuco Beach
    Cumbuco Beach is a popular coastal destination in northeastern Brazil known for its sand dunes, strong winds, and water sports like kitesurfing and windsurfing.
  • 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_69e0c47e2e5c81909a7f74ce3de50911 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f12420b1cc81909b375891aedc0979 completed April 28, 2026, 9:18 p.m.
Created at: April 16, 2026, 7:55 p.m.