Triple

T1843657
Position Surface form Disambiguated ID Type / Status
Subject CR Vasco da Gama E41234 entity
Predicate shortName P43 FINISHED
Object Vasco E41234 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: Vasco | Statement: [CR Vasco da Gama, shortName, Vasco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vasco
Context triple: [CR Vasco da Gama, shortName, Vasco]
  • A. Santos
    Santos is a common Portuguese surname shared by numerous notable figures in politics, sports, and the arts across Portuguese-speaking countries.
  • B. Santos
    Santos is a major Brazilian port city on the coast of São Paulo state, known for its extensive coffee export history and popular beachfront.
  • C. CR Vasco da Gama chosen
    CR Vasco da Gama is a traditional and historically successful Brazilian football club based in Rio de Janeiro, known for its passionate fanbase and significant role in the country’s sporting culture.
  • D. Vélez
    Vélez is a municipality in Colombia’s Santander Department known for its colonial heritage and traditional sweets.
  • E. Vélez
    Vélez is a Spanish-language surname common in Latin America and Spain, borne by various notable figures in arts, sports, and public life.
  • 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_69a88648cd44819093303206d96d76ad completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb04eb0748190b226f932e544925f completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc9be1ef481909cd6f6975bf2165d completed March 8, 2026, 7:10 p.m.
Created at: March 4, 2026, 7:33 p.m.