Triple

T614493
Position Surface form Disambiguated ID Type / Status
Subject Belgian diaspora E12172 entity
Predicate hasCommunityIn P17132 FINISHED
Object São Paulo E9033 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: São Paulo | Statement: [Belgian diaspora, hasCommunityIn, São Paulo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: São Paulo
Context triple: [Belgian diaspora, hasCommunityIn, São Paulo]
  • A. São Paulo chosen
    São Paulo is Brazil’s largest city and a major global financial, cultural, and industrial center in South America.
  • B. Rio de Janeiro
    Rio de Janeiro is a major Brazilian coastal city famed for its stunning beaches, dramatic landscape, Carnival festival, and iconic Christ the Redeemer statue.
  • C. Campinas
    Campinas is a major city in the state of São Paulo, Brazil, known as an important industrial, technological, and transportation hub in the country.
  • D. Recife
    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.
  • E. Brasília
    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.
  • 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_69a493309df48190a327f748e88049a6 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a4a514b514819088e7b6b7e4675905 completed March 1, 2026, 8:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a5554937a081909967f5298dbe1082 completed March 2, 2026, 9:15 a.m.
Created at: March 1, 2026, 7:35 p.m.