Triple

T6008430
Position Surface form Disambiguated ID Type / Status
Subject Mato Grosso do Sul E133771 entity
Predicate borders P224 FINISHED
Object Goiás E370836 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: Goiás | Statement: [Mato Grosso do Sul, borders, Goiás]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Goiás
Context triple: [Mato Grosso do Sul, borders, Goiás]
  • A. Goiás chosen
    Goiás is a large inland state in central Brazil known for its agricultural production, Cerrado savanna landscapes, and the regional capital city of Goiânia.
  • 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. Minas Gerais
    Minas Gerais is a large, historically rich state in southeastern Brazil known for its colonial-era towns, mining heritage, and significant cultural and architectural landmarks.
  • D. 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.
  • E. Piauí
    Piauí is a state in northeastern Brazil known for its semi-arid landscapes, short Atlantic coastline, and rich archaeological sites such as those in Serra da Capivara National Park.
  • 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_69c00872444c8190bfaf1739dcec765c completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c04f154ca481909431baf4feecc16d completed March 22, 2026, 8:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11367b1e88190ab8671ec48953663 completed March 23, 2026, 10:18 a.m.
Created at: March 22, 2026, 4:06 p.m.