Triple

T9597775
Position Surface form Disambiguated ID Type / Status
Subject Paraíba do Sul River E231774 entity
Predicate passesThrough P225 FINISHED
Object Volta Redonda E250440 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: Volta Redonda | Statement: [Paraíba do Sul River, passesThrough, Volta Redonda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Volta Redonda
Context triple: [Paraíba do Sul River, passesThrough, Volta Redonda]
  • A. Volta Redonda chosen
    Volta Redonda is an industrial city in southeastern Brazil best known for its major steel production complex and role in the country’s metallurgical sector.
  • B. Resende
    Resende is a Portuguese municipality in the Douro region, known for its scenic river landscapes and production of cherries and vinho verde.
  • C. Teresópolis
    Teresópolis is a mountainous city in the state of Rio de Janeiro, Brazil, known for its cool climate, natural parks, and role as a popular ecotourism and weekend getaway destination.
  • D. Macaé
    Macaé is a coastal city in southeastern Brazil known for its offshore oil industry and role as a major hub for petroleum exploration.
  • E. Cumbuco
    Cumbuco is a coastal village in northeastern Brazil known for its sand dunes, lagoons, and strong winds that make it a popular destination for kitesurfing and other beach tourism.
  • 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_69ca8484838c8190b2049199d22fef70 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9a366d3481908db62e476958eafe completed April 1, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69d190dd38e48190aef80bb7a153bff6 completed April 4, 2026, 10:29 p.m.
Created at: March 30, 2026, 8:07 p.m.