Triple

T16722983
Position Surface form Disambiguated ID Type / Status
Subject Champion Sound E406394 entity
Predicate featuresArtist P1952 FINISHED
Object Frank-N-Dank E566118 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: Frank-N-Dank | Statement: [Champion Sound, featuresArtist, Frank-N-Dank]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frank-N-Dank
Context triple: [Champion Sound, featuresArtist, Frank-N-Dank]
  • A. Frank-N-Dank chosen
    Frank-N-Dank is a Detroit hip hop duo known for their close collaboration with producer J Dilla and their raw, energetic underground rap style.
  • B. Fu-Schnickens
    Fu-Schnickens was an early 1990s American hip hop group known for their fast-paced, tongue-twisting raps and playful, Afrocentric style.
  • C. Danko
    Danko is a surname most notably associated with Rick Danko, the Canadian musician and bassist for the influential rock group The Band.
  • D. FANK
    FANK was the acronym for the Khmer National Armed Forces, the military of the pro-U.S. Lon Nol government in Cambodia during the Cambodian Civil War.
  • E. Frank the sausage
    Frank the sausage is the hot dog protagonist of the adult animated film "Sausage Party," known for questioning his supermarket reality and seeking the truth about what happens to food after purchase.
  • 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_69d8838f242881908abd8bc138795886 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e387449eb08190b174f8e142ea631b completed April 18, 2026, 1:29 p.m.
NED1 Entity disambiguation (via context triple) batch_6a009d43c49081908eca922da8f90793 completed May 10, 2026, 2:59 p.m.
Created at: April 10, 2026, 5:20 a.m.