Triple

T12259489
Position Surface form Disambiguated ID Type / Status
Subject Once Upon a Time E292183 entity
Predicate featuresArtist P1952 FINISHED
Object Busy Signal E376364 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: Busy Signal | Statement: [Once Upon a Time, featuresArtist, Busy Signal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Busy Signal
Context triple: [Once Upon a Time, featuresArtist, Busy Signal]
  • A. Busy Signal chosen
    Busy Signal is a Jamaican dancehall and reggae artist known for his energetic delivery and hits that blend hardcore dancehall with reggae and global pop influences.
  • B. Get Busy
    "Get Busy" is a 2003 dancehall hit single by Jamaican artist Sean Paul that became one of his most internationally successful and recognizable songs.
  • C. Get Busy
    "Get Busy" is a track by hip-hop band The Roots, featured on their politically charged 2008 album "Rising Down."
  • D. Signal
    Signal is a Canadian publishing imprint known for releasing thought-provoking non-fiction works on contemporary issues.
  • E. Signal
    Signal is a privacy-focused messaging app known for its strong end-to-end encryption and open-source protocol.
  • 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_69d6ab6856488190b5d31178d5015f8e completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91cd964ec81908241d2b9a96d1025 completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60ac1b5148190838b782848e3fa36 completed May 2, 2026, 2:31 p.m.
Created at: April 8, 2026, 9:52 p.m.