Triple

T893389
Position Surface form Disambiguated ID Type / Status
Subject Brazil E19289 entity
Predicate majorCity P316 FINISHED
Object Recife E24891 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: Recife | Statement: [Brazil, majorCity, Recife]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Recife
Context triple: [Brazil, majorCity, Recife]
  • A. Recife chosen
    Recife is a major coastal city in northeastern Brazil known for its historic colonial architecture, extensive waterways, and role as an important cultural and economic center.
  • B. 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.
  • C. Olinda
    Olinda is a historic coastal city in northeastern Brazil renowned for its well-preserved colonial architecture and vibrant Carnival celebrations.
  • D. 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.
  • E. Salvador
    Salvador is the given name of the renowned Spanish surrealist artist Salvador Dalí.
  • 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_69a4939d37188190848be3d426ebc9ae completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ad212cd8819091eb1b7d606f5afd completed March 1, 2026, 9:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac257f3b2c819082a16c7242d89404 completed March 7, 2026, 1:17 p.m.
Created at: March 1, 2026, 7:39 p.m.