Triple

T5047601
Position Surface form Disambiguated ID Type / Status
Subject Tapajós River E113704 entity
Predicate flowsThrough P225 FINISHED
Object Pará 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 | Statement: [Tapajós River, flowsThrough, Pará]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pará
Context triple: [Tapajós River, flowsThrough, Pará]
  • 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. Amapá
    Amapá is a sparsely populated state in northern Brazil, located in the Amazon region along the Atlantic coast and bordering French Guiana.
  • C. 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.
  • 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. 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.
  • 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_69bd44391fc48190a311ce9c826c209b completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd740002b48190bc7aa176d734c589 completed March 20, 2026, 4:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9c9143a081909132c66eb9fc91db completed March 21, 2026, 1:26 p.m.
Created at: March 20, 2026, 1:37 p.m.