Triple

T6776921
Position Surface form Disambiguated ID Type / Status
Subject Paresí language E155580 entity
Predicate spokenIn P2266 FINISHED
Object Mato Grosso E489604 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: Mato Grosso | Statement: [Paresí language, spokenIn, Mato Grosso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mato Grosso
Context triple: [Paresí language, spokenIn, Mato Grosso]
  • A. Mato Grosso chosen
    Mato Grosso is a large inland state in west-central Brazil known for its vast Amazon rainforest, Pantanal wetlands, and agricultural frontier.
  • B. Rondônia
    Rondônia is a state in northern Brazil known for its Amazon rainforest areas, agricultural frontier, and diverse immigrant communities, including a significant population of German Brazilians.
  • C. Tocantins
    Tocantins is a central Brazilian state known for its relatively recent creation in 1988, its capital Palmas, and its mix of Amazonian and cerrado ecosystems.
  • D. Pará
    Pará is a large state in northern Brazil known for its Amazon rainforest, rich biodiversity, and the major port city of Belém.
  • E. 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.
  • 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_69c688162bf8819088b664b5c3b5be7a completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d26725208190b64935cfd08b2aff completed March 27, 2026, 6:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c748a839648190a2d6875a8465579b completed March 28, 2026, 3:19 a.m.
Created at: March 27, 2026, 2:13 p.m.