Triple

T12050234
Position Surface form Disambiguated ID Type / Status
Subject Line 4–Yellow E286895 entity
Predicate hasStation P35 FINISHED
Object Pinheiros E923632 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: Pinheiros | Statement: [Line 4–Yellow, hasStation, Pinheiros]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pinheiros
Context triple: [Line 4–Yellow, hasStation, Pinheiros]
  • A. Pinheiros, São Paulo chosen
    Pinheiros is a central and upscale district in São Paulo known for its vibrant nightlife, diverse gastronomy, cultural venues, and proximity to major business and residential areas.
  • B. Santo Amaro
    Santo Amaro is a central neighborhood in Recife, Brazil, known for its mix of residential areas, commerce, and important urban infrastructure.
  • C. Cidade Jardim
    Cidade Jardim is a residential neighborhood and planned development located within the Barra da Tijuca region of Rio de Janeiro, Brazil.
  • D. Santo Amaro das Brotas
    Santo Amaro das Brotas is a municipality in the Brazilian state of Sergipe known for its riverside landscapes and traditional rural culture.
  • E. Mogi das Cruzes
    Mogi das Cruzes is a municipality in southeastern Brazil known as part of the Greater São Paulo metropolitan area and recognized for its industrial activity and agricultural production.
  • 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_69d6ab4780948190bdb9f7620c2ac27e completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d904227958819084dbd5eb2566c735 completed April 10, 2026, 2:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6345319808190a68195e215c2bd80 completed May 2, 2026, 5:28 p.m.
Created at: April 8, 2026, 9:47 p.m.