Triple

T5494763
Position Surface form Disambiguated ID Type / Status
Subject 1950 FIFA World Cup E144184 entity
Predicate hostCity P1798 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: [1950 FIFA World Cup, hostCity, São Paulo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: São Paulo
Context triple: [1950 FIFA World Cup, hostCity, 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. Sé, São Paulo
    Sé, São Paulo is a historic central district of São Paulo, Brazil, known as the city's symbolic heart and home to major landmarks, including the main cathedral and the official city center marker.
  • C. 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.
  • D. Guarulhos
    Guarulhos is a major city in the São Paulo metropolitan area of Brazil, known as an important industrial and logistics hub.
  • E. San Pablo
    San Pablo is a city in the province of Laguna in the Philippines, known for its seven crater lakes and role as a commercial and cultural hub in the Southern Tagalog region.
  • 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_69c008f5a2748190bce7a39aabf87a6d completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01b8c05ac8190999f84c33719d794 completed March 22, 2026, 4:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0277e577481909f1559082e482995 completed March 22, 2026, 5:31 p.m.
Created at: March 22, 2026, 3:31 p.m.