Triple

T1260039
Position Surface form Disambiguated ID Type / Status
Subject Pantanal E12476 entity
Predicate countrySubdivision P766 FINISHED
Object Mato Grosso E74770 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: [Pantanal, countrySubdivision, Mato Grosso]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mato Grosso
Context triple: [Pantanal, countrySubdivision, Mato Grosso]
  • A. Pará
    Pará is a large state in northern Brazil known for its Amazon rainforest, rich biodiversity, and the major port city of Belém.
  • 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. Mato Grosso region of Brazil chosen
    The Mato Grosso region of Brazil is a vast, sparsely populated area in west-central Brazil known for its dense rainforests, remote wilderness, and role as a historic frontier for explorers and adventurers.
  • D. Bahia
    Bahia is a traditional Brazilian football club based in Salvador, known for its passionate fanbase and historic success in national competitions.
  • E. Cuiabá
    Cuiabá is the capital city of Brazil’s Mato Grosso state and a primary urban hub and access point for exploring the Pantanal wetlands.
  • 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_69a4933352e08190ac617291985e76c0 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4bfc503e88190b237210a61228dd8 completed March 1, 2026, 10:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad67f9b0dc8190a5b38450c227eac5 completed March 8, 2026, 12:13 p.m.
Created at: March 1, 2026, 7:50 p.m.