Triple

T13718405
Position Surface form Disambiguated ID Type / Status
Subject Born 2 Rap E328960 entity
Predicate hasTrack P3284 FINISHED
Object Stay Down E739426 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: Stay Down | Statement: [Born 2 Rap, hasTrack, Stay Down]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stay Down
Context triple: [Born 2 Rap, hasTrack, Stay Down]
  • A. Stay Down chosen
    "Stay Down" is a track by American rapper Big Sean from his critically acclaimed 2015 album *Dark Sky Paradise*.
  • B. Get Down
    "Get Down" is a 1994 hip hop single by Craig Mack, best known for its remix featuring The Notorious B.I.G. and its classic Bad Boy Records sound.
  • C. Get Down
    "Get Down" is a notable track by the hip-hop band The Roots, showcasing their signature blend of live instrumentation and socially conscious lyricism.
  • D. Still Down
    "Still Down" is a music production or song project associated with American record producer Happy Perez, known for his work in R&B and hip-hop.
  • E. Down There
    "Down There" is a 1956 crime novel by David Goodis, known for its bleak, noir portrayal of a former concert pianist drawn into the criminal underworld and later adapted into François Truffaut’s film "Shoot the Piano Player."
  • 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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dd439a121c81908cae964e7756274c completed April 13, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69f79d5a23bc8190942568658665bbb0 completed May 3, 2026, 7:09 p.m.
Created at: April 9, 2026, 9:55 p.m.