Triple

T7345578
Position Surface form Disambiguated ID Type / Status
Subject Fordlandia E169370 entity
Predicate setting P1957 FINISHED
Object Pará, Brazil E169954 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: Pará, Brazil | Statement: [Fordlandia, setting, Pará, Brazil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pará, Brazil
Context triple: [Fordlandia, setting, Pará, Brazil]
  • A. Pará chosen
    Pará is a large state in northern Brazil known for its Amazon rainforest, rich biodiversity, and the major port city of Belém.
  • B. Amazonas state
    Amazonas state is Brazil’s largest and mostly rainforest-covered state in the northwest of the country, known for encompassing much of the Amazon River basin and the city of Manaus.
  • C. Roraima state
    Roraima state is Brazil’s northernmost and least populated state, located in the Amazon region and known for its vast savannas, indigenous communities, and the iconic Mount Roraima.
  • D. 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.
  • E. Mato Grosso
    Mato Grosso is a large inland state in west-central Brazil known for its vast Amazon rainforest, Pantanal wetlands, and agricultural frontier.
  • 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_69c68a57710481909f0c1f3c6ebdb6f2 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f0eeb30081909d25704ac9b49d0e completed March 27, 2026, 9:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7fa8de0888190b62101471048b8e1 completed March 28, 2026, 3:58 p.m.
Created at: March 27, 2026, 3:05 p.m.