Triple

T12312287
Position Surface form Disambiguated ID Type / Status
Subject Taboão da Serra E293508 entity
Predicate hasBorderWith P224 FINISHED
Object Itapecerica da Serra E367723 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: Itapecerica da Serra | Statement: [Taboão da Serra, hasBorderWith, Itapecerica da Serra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Itapecerica da Serra
Context triple: [Taboão da Serra, hasBorderWith, Itapecerica da Serra]
  • A. Itapecerica da Serra chosen
    Itapecerica da Serra is a municipality in the metropolitan region of São Paulo, Brazil, known for its hilly terrain and remaining areas of Atlantic Forest.
  • B. Taquaritinga
    Taquaritinga is a municipality in the interior of Brazil’s São Paulo state, known for its agricultural production and regional commerce.
  • C. Indaiatuba
    Indaiatuba is a rapidly growing municipality in southeastern Brazil known for its strong industrial base, high quality of life, and proximity to the city of Campinas.
  • D. Laranjal Paulista
    Laranjal Paulista is a municipality in the state of São Paulo, Brazil, known for its riverside setting and regional agricultural activities.
  • E. Bragança Paulista
    Bragança Paulista is a municipality in southeastern Brazil known for its historical architecture, mild climate, and role as a regional commercial and educational center.
  • 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_69d6ab6a2b50819082f6aedd32ed608a completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f03d3c88190baedffb83465bff8 completed April 10, 2026, 6:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5e627b4819084c830f4a46a8cda completed May 3, 2026, 4:58 a.m.
Created at: April 8, 2026, 9:53 p.m.