Triple

T14498102
Position Surface form Disambiguated ID Type / Status
Subject Cubatão E359555 entity
Predicate borderedBy P224 FINISHED
Object Bertioga E139027 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: Bertioga | Statement: [Cubatão, borderedBy, Bertioga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bertioga
Context triple: [Cubatão, borderedBy, Bertioga]
  • A. Bertioga chosen
    Bertioga is a coastal municipality in the state of São Paulo, Brazil, known for its beaches and Atlantic Forest landscapes.
  • B. Papelotte
    Papelotte is a farmhouse and hamlet in Belgium that served as a key defensive position on the Allied left flank during the Battle of Waterloo in 1815.
  • C. Port-Bouët
    Port-Bouët is a coastal commune and suburb of Abidjan in Côte d'Ivoire, known for hosting the Félix-Houphouët-Boigny International Airport and several key port and beach areas.
  • D. Port Pierre Canto
    Port Pierre Canto is a prominent marina in Cannes, France, known for hosting luxury yachts and offering upscale waterfront amenities along the French Riviera.
  • E. Lagrenée
    Lagrenée is a French surname most notably associated with the 18th-century painter Louis Lagrenée.
  • 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_69d8279740308190af9df93a3af8592e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de9311cc748190880c784f173b7f2b completed April 14, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6d99a7948190a3ff01e7b74aaa1e completed May 8, 2026, 4:59 a.m.
Created at: April 10, 2026, 1:21 a.m.