Triple

T2522283
Position Surface form Disambiguated ID Type / Status
Subject Horizontina E55549 entity
Predicate hasMunicipalStatusIn P21214 FINISHED
Object Rio Grande do Sul E208924 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: Rio Grande do Sul | Statement: [Horizontina, hasMunicipalStatusIn, Rio Grande do Sul]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rio Grande do Sul
Context triple: [Horizontina, hasMunicipalStatusIn, Rio Grande do Sul]
  • A. Rio Grande do Sul chosen
    Rio Grande do Sul is Brazil’s southernmost state, known for its gaucho culture, strong agricultural economy, and shared borders with Uruguay and Argentina.
  • B. Mato Grosso do Sul
    Mato Grosso do Sul is a landlocked state in Brazil’s Center-West region, known for its vast Pantanal wetlands, rich biodiversity, and cattle ranching economy.
  • C. Paraná state
    Paraná state is a southern Brazilian state known for its diverse landscapes, major agricultural production, and popular natural attractions including part of the Iguaçu National Park.
  • D. Santa Catarina
    Santa Catarina is an industrial and residential city in the Monterrey metropolitan area of the Mexican state of Nuevo León.
  • E. Santa Catarina
    Santa Catarina is a neighborhood in Mexico City known for its residential character and proximity to the Miguel Ángel de Quevedo metro station.
  • 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_69ab49e4749c8190813311efd1630f1b completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd23895348190bb4dad6d7174893a completed March 7, 2026, 7:22 a.m.
NED1 Entity disambiguation (via context triple) batch_69af6550c55481908fe4e8bab17aaa6d completed March 10, 2026, 12:26 a.m.
Created at: March 6, 2026, 9:46 p.m.