Triple

T8795392
Position Surface form Disambiguated ID Type / Status
Subject ICMBio E209276 entity
Predicate headquartersLocation P62 FINISHED
Object Brasília E34115 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: Brasília | Statement: [ICMBio, headquartersLocation, Brasília]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brasília
Context triple: [ICMBio, headquartersLocation, Brasília]
  • A. Brasília chosen
    Brasília is the modernist-planned capital city of Brazil, known for its distinctive architecture and role as a major political and administrative center in South America.
  • B. Belo Horizonte
    Belo Horizonte is the capital and largest city of the Brazilian state of Minas Gerais, known for its modernist architecture, surrounding mountains, and vibrant cultural and economic life.
  • C. Manaus
    Manaus is a major Brazilian city and capital of the state of Amazonas, known as a key gateway to the Amazon rainforest and an important industrial and cultural center in the region.
  • D. Belém
    Belém is a historic riverside district of Lisbon, Portugal, known for its monuments of the Age of Discoveries, including the Belém Tower and Jerónimos Monastery.
  • E. Brasília Teimosa
    Brasília Teimosa is a coastal neighborhood in Recife, Brazil, known for its working-class roots, history of informal settlement, and vibrant seaside community.
  • 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_69ca836240888190a62b262e56a69d2f completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fa0c6008190a5c4d87510ad5bbd completed March 31, 2026, 11:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6f532ed48190a21996f865428831 completed April 3, 2026, 7:42 a.m.
Created at: March 30, 2026, 6:43 p.m.