Triple
T8008790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glitter |
E186429
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | GOOD Music |
E5585
|
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: GOOD Music | Statement: [Glitter, associatedAct, GOOD Music]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: GOOD Music Context triple: [Glitter, associatedAct, GOOD Music]
-
A.
GOOD Music
chosen
GOOD Music is a record label founded by Kanye West that is known for its roster of influential hip-hop and R&B artists.
-
B.
GOOD Music: The Album
GOOD Music: The Album is a collaborative compilation project by artists from Kanye West’s G.O.O.D. Music label, showcasing the roster’s collective sound and style.
-
C.
Big Music
Big Music is a studio album by the Scottish rock band Simple Minds, showcasing their anthemic, synth-infused sound in a modern context.
-
D.
Soundgasm
Soundgasm is a popular Afrobeats song by Nigerian artist Rema, known for its sensual lyrics and smooth, melodic production.
-
E.
Good Vibes
Good Vibes is an animated television series known for its raunchy teen comedy set in a Southern California surf town.
- 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_69ca82abaffc8190ab8af79cdbc31ab3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3d6f76408190a1312369521a187a |
completed | March 31, 2026, 3:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc566604e881908792c7155a370e4c |
completed | March 31, 2026, 11:19 p.m. |
Created at: March 30, 2026, 5:19 p.m.