Triple

T17976659
Position Surface form Disambiguated ID Type / Status
Subject Let the Groove Get In E449491 entity
Predicate writer P1360 FINISHED
Object Gracinha Leporace NE NERFINISHED

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: Gracinha Leporace | Statement: [Let the Groove Get In, writer, Gracinha Leporace]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gracinha Leporace
Context triple: [Let the Groove Get In, writer, Gracinha Leporace]
  • A. Gracinha Leporace chosen
    Gracinha Leporace is a Brazilian singer known for her long-time collaborations with Sérgio Mendes and contributions to Brazilian popular and jazz music.
  • B. Gisela Rossi
    Gisela Rossi is known as the former spouse of the late commodities trader and financier Marc Rich.
  • C. Ana Maria Camargo
    Ana Maria Camargo is a Brazilian television presenter and journalist known for her work on news and talk shows.
  • D. Sheila Lirio Marcelo
    Sheila Lirio Marcelo is a Filipino-American entrepreneur best known as the founder and former CEO of Care.com, a leading online marketplace for caregiving services.
  • E. Carla Quevedo
    Carla Quevedo is an Argentine actress known for her work in both Latin American and U.S. film and television, including roles in acclaimed dramas and crime series.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f9927c8190a006110c8b996e61 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4b20010c8819088c022565183a7ff completed April 19, 2026, 10:44 a.m.
Created at: April 10, 2026, 10:22 a.m.