Triple

T7729014
Position Surface form Disambiguated ID Type / Status
Subject Companhia das Letras E175203 entity
Predicate location P40 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: [Companhia das Letras, location, São Paulo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: São Paulo
Context triple: [Companhia das Letras, location, 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_69c6995e912c81909a49a2657103f786 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c703170650819095a1b073d67d231d completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8b52adf6481908cb78e7cc7c4266d completed March 29, 2026, 5:14 a.m.
Created at: March 27, 2026, 4:06 p.m.