Triple

T19220991
Position Surface form Disambiguated ID Type / Status
Subject Roraima E480611 entity
Predicate borderWith P224 FINISHED
Object Amazonas (Brazilian state) NE NERFINISHED

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: Amazonas (Brazilian state) | Statement: [Roraima, borderWith, Amazonas (Brazilian state)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amazonas (Brazilian state)
Context triple: [Roraima, borderWith, Amazonas (Brazilian state)]
  • A. Amazonas state chosen
    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.
  • B. Amazonas state
    Amazonas state is a vast, sparsely populated region in southern Venezuela known for its Amazon rainforest, indigenous communities, and rich biodiversity.
  • 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. Marabá
    Marabá is a major industrial and commercial city in southeastern Pará, Brazil, known for its role in mining, steel production, and as a regional transportation hub.
  • E. Amazonas mesoregion
    The Amazonas mesoregion is a large administrative and geographic subdivision in the Brazilian state of Amazonas, encompassing vast areas of rainforest and sparsely populated municipalities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8cb8c348190b52075823911c869 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fa3fa9348190920f9d41b8beb900 completed April 20, 2026, 10:04 a.m.
Created at: April 10, 2026, 1:24 p.m.