Triple

T12707115
Position Surface form Disambiguated ID Type / Status
Subject Rodovia Dom Pedro I E303616 entity
Predicate connects P390 FINISHED
Object Atibaia E370647 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: Atibaia | Statement: [Rodovia Dom Pedro I, connects, Atibaia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Atibaia
Context triple: [Rodovia Dom Pedro I, connects, Atibaia]
  • A. Atibaia chosen
    Atibaia is a municipality in southeastern Brazil known for its mild climate, flower and strawberry production, and proximity to São Paulo city.
  • B. Itanhaém
    Itanhaém is a coastal municipality in southeastern Brazil known for its beaches, historic colonial center, and tourism along the São Paulo state shoreline.
  • C. Taubaté
    Taubaté is a historic industrial and educational city in southeastern Brazil, located in the Paraíba Valley between São Paulo and Rio de Janeiro.
  • D. Barretos
    Barretos is a municipality in the Brazilian state of São Paulo, widely known for hosting one of the largest annual rodeo festivals in Latin America.
  • E. Criciúma
    Criciúma is an industrial city in southern Brazil known for its coal mining heritage and ceramics 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_69d7bdef90d48190b46b88270e780946 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9620663e881908d367170ed6d2c81 completed April 10, 2026, 8:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671b648f48190a29924c484713fc7 completed May 2, 2026, 9:50 p.m.
Created at: April 9, 2026, 5:23 p.m.