Triple

T4990653
Position Surface form Disambiguated ID Type / Status
Subject Madeira River E112120 entity
Predicate flowsThrough P225 FINISHED
Object Rondônia E280499 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: Rondônia | Statement: [Madeira River, flowsThrough, Rondônia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rondônia
Context triple: [Madeira River, flowsThrough, Rondônia]
  • A. Rondônia chosen
    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.
  • B. 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.
  • C. Pará
    Pará is a large state in northern Brazil known for its Amazon rainforest, rich biodiversity, and the major port city of Belém.
  • D. 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.
  • E. Amapá
    Amapá is a sparsely populated state in northern Brazil, located in the Amazon region along the Atlantic coast and bordering French Guiana.
  • 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_69bd441be7bc8190b530362d427b97d2 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd728141d48190a0713e6d33c50fb6 completed March 20, 2026, 4:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69be8a282dd08190a29b92e8e825a3bb completed March 21, 2026, 12:08 p.m.
Created at: March 20, 2026, 1:34 p.m.