Triple

T5486834
Position Surface form Disambiguated ID Type / Status
Subject Ribatejo E123602 entity
Predicate borders P224 FINISHED
Object Beira Litoral E76438 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: Beira Litoral | Statement: [Ribatejo, borders, Beira Litoral]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beira Litoral
Context triple: [Ribatejo, borders, Beira Litoral]
  • A. Beira Litoral chosen
    Beira Litoral was a former central coastal province of Portugal that included the city of Coimbra and stretched between the Atlantic Ocean and the interior regions.
  • B. Baixada Santista
    Baixada Santista is a coastal metropolitan region in the state of São Paulo, Brazil, known for its port city of Santos, beaches, and significant economic and touristic activity.
  • C. Beira Alta
    Beira Alta is a historical province in north-central Portugal known for its mountainous landscapes, fortified towns, and wine-producing regions.
  • D. Região dos Lagos
    Região dos Lagos is a coastal tourist region in the state of Rio de Janeiro, Brazil, known for its beaches, clear waters, and popular resort towns like Cabo Frio, Arraial do Cabo, and Búzios.
  • E. Southeast Region of Brazil
    The Southeast Region of Brazil is the country’s most populous and economically developed area, encompassing major states and cities such as São Paulo, Rio de Janeiro, and Minas Gerais.
  • 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_69bd464a2d908190869324ce176779c8 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd92639b3481908845c280d334117f completed March 20, 2026, 6:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf48aa12708190add69c5fd51d161d completed March 22, 2026, 1:40 a.m.
Created at: March 20, 2026, 2:10 p.m.