Triple

T11893711
Position Surface form Disambiguated ID Type / Status
Subject Interlagos E282981 entity
Predicate hasCorner P42380 FINISHED
Object Bico de Pato E953587 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: Bico de Pato | Statement: [Interlagos, hasCorner, Bico de Pato]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bico de Pato
Context triple: [Interlagos, hasCorner, Bico de Pato]
  • A. Bico de Pato chosen
    Bico de Pato is a tight, slow-speed hairpin-style corner at Brazil’s Autódromo José Carlos Pace (Interlagos) known for heavy braking and overtaking opportunities.
  • B. Pato
    Pato is a Galician musician and educator best known internationally as a virtuoso gaita (Galician bagpipe) player and collaborator with jazz and classical ensembles.
  • C. Pato
    Pato is the stage name of Patrice Wilson, a Nigerian-American music producer and songwriter best known for creating viral pop songs such as Rebecca Black’s “Friday.”
  • D. Pato
    Pato is the nickname for the Talgo 350, a high-speed Spanish train known for its distinctive duck-bill-shaped nose and use on AVE services.
  • E. Goose
    Goose was the nickname of Leon "Goose" Goslin, a Hall of Fame American Major League Baseball left fielder known for his powerful hitting in the 1920s and 1930s.
  • 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_69d6ab2a90b08190a4e818821cc93e6d completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8dd1172988190a2c13d37220f2f93 completed April 10, 2026, 11:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69f43fe43c7c8190a85d464fd48e00d9 completed May 1, 2026, 5:53 a.m.
Created at: April 8, 2026, 9:44 p.m.