Triple

T9178602
Position Surface form Disambiguated ID Type / Status
Subject choro E220262 entity
Predicate notableWork P4 FINISHED
Object Brasileirinho
"Brasileirinho" is a famous and virtuosic Brazilian choro composition, widely regarded as a classic of the genre and a showcase for instrumental skill.
E782183 NE FINISHED

How this triple was built (4 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: Brasileirinho | Statement: [choro, notableWork, Brasileirinho]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brasileirinho
Context triple: [choro, notableWork, Brasileirinho]
  • A. Maracanãzinho
    Maracanãzinho is an iconic indoor arena in Rio de Janeiro, Brazil, renowned for hosting major international volleyball and basketball events.
  • B. Cariocão
    Cariocão is the popular nickname for the Campeonato Carioca, the top professional football championship of the state of Rio de Janeiro in Brazil.
  • C. Tostão
    Tostão is a legendary Brazilian forward who starred alongside Pelé in Brazil’s iconic 1970 World Cup–winning team and is regarded as one of the country’s greatest footballers.
  • D. Raminho
    Raminho is a civil parish located in the municipality of Angra do Heroísmo on Terceira Island in the Azores, Portugal.
  • E. Piquinho
    Piquinho is the prominent summit cone at the top of Mount Pico in the Azores, known as the highest point in Portugal.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Brasileirinho
Triple: [choro, notableWork, Brasileirinho]
Generated description
"Brasileirinho" is a famous and virtuosic Brazilian choro composition, widely regarded as a classic of the genre and a showcase for instrumental skill.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Brasileirinho
Target entity description: "Brasileirinho" is a famous and virtuosic Brazilian choro composition, widely regarded as a classic of the genre and a showcase for instrumental skill.
  • A. Maracanãzinho
    Maracanãzinho is an iconic indoor arena in Rio de Janeiro, Brazil, renowned for hosting major international volleyball and basketball events.
  • B. Cariocão
    Cariocão is the popular nickname for the Campeonato Carioca, the top professional football championship of the state of Rio de Janeiro in Brazil.
  • C. Tostão
    Tostão is a legendary Brazilian forward who starred alongside Pelé in Brazil’s iconic 1970 World Cup–winning team and is regarded as one of the country’s greatest footballers.
  • D. Raminho
    Raminho is a civil parish located in the municipality of Angra do Heroísmo on Terceira Island in the Azores, Portugal.
  • E. Piquinho
    Piquinho is the prominent summit cone at the top of Mount Pico in the Azores, known as the highest point in Portugal.
  • F. None of above. chosen

Provenance (5 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_69ca83e589948190ac9907819db11ddf completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccc24eeb988190af82dfba49aac2f8 completed April 1, 2026, 6:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69d054ae9a708190b26c2f2c7ebb59c9 completed April 4, 2026, midnight
NEDg Description generation batch_69d05571243c8190bd7fcc6e675b3500 completed April 4, 2026, 12:04 a.m.
NED2 Entity disambiguation (via description) batch_69d0564391cc81909c0cea2d49c38fb4 completed April 4, 2026, 12:07 a.m.
Created at: March 30, 2026, 7:23 p.m.