Triple

T7369372
Position Surface form Disambiguated ID Type / Status
Subject Pará E169954 entity
Predicate borderedBy P224 FINISHED
Object Amapá E171661 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: Amapá | Statement: [Pará, borderedBy, Amapá]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amapá
Context triple: [Pará, borderedBy, Amapá]
  • A. Amapá chosen
    Amapá is a sparsely populated state in northern Brazil, located in the Amazon region along the Atlantic coast and bordering French Guiana.
  • B. Pará
    Pará is a large state in northern Brazil known for its Amazon rainforest, rich biodiversity, and the major port city of Belém.
  • C. Maranhão
    Maranhão is a northeastern Brazilian state known for its colonial heritage, Afro-Brazilian culture, and the Lençóis Maranhenses dune and lagoon landscapes.
  • D. 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.
  • E. 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.
  • 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_69c68a5ade988190885b7175f63b7534 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f1810668819094aec4b237d08068 completed March 27, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8276ec3b88190b720354787f7a735 completed March 28, 2026, 7:09 p.m.
Created at: March 27, 2026, 3:07 p.m.