Triple

T6572605
Position Surface form Disambiguated ID Type / Status
Subject Vila do Bispo E155477 entity
Predicate contains P35 FINISHED
Object Raposeira E528985 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: Raposeira | Statement: [Vila do Bispo, contains, Raposeira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Raposeira
Context triple: [Vila do Bispo, contains, Raposeira]
  • A. Raposeira chosen
    Raposeira is a small village in Portugal’s Algarve region, known for its rural charm and proximity to the Atlantic coast near Vila do Bispo.
  • B. Coruripe
    Coruripe is a coastal municipality in northeastern Brazil known for its beaches, fishing activities, and sugarcane agriculture.
  • C. Bérrio
    Bérrio was a Portuguese carrack that served as one of the ships in Vasco da Gama’s pioneering fleet on the first voyage from Portugal to India.
  • D. Tamarineira
    Tamarineira is a neighborhood in the Brazilian city of Recife, known for its residential areas and local commerce.
  • E. Mairiporã
    Mairiporã is a municipality in southeastern Brazil known for its mountainous landscapes, proximity to the Cantareira State Park, and role as a green retreat near the São Paulo metropolitan area.
  • 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_69c688151254819080387f87deab8fa7 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ae6faa3c81908f1777d616cece46 completed March 27, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6d56a7de88190948fdd052dd4d5d5 completed March 27, 2026, 7:07 p.m.
Created at: March 27, 2026, 1:53 p.m.