Triple
T27050337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medicine Music |
E684746
|
entity |
| Predicate | featuresVocalTechniques |
P118643
|
FINISHED |
| Object | a cappella vocals |
—
|
LITERAL 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: a cappella vocals | Statement: [Medicine Music, featuresVocalTechniques, a cappella vocals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresVocalTechniques Context triple: [Medicine Music, featuresVocalTechniques, a cappella vocals]
-
A.
featuresVocal
Indicates that one entity includes or presents the vocal performance or voice of another entity.
-
B.
vocaleseTechnique
Indicates a relationship where a performer uses the vocalese technique, setting lyrics to pre-existing instrumental melodies or improvised solos.
-
C.
featuresVocalPercussion
chosen
Indicates that the subject includes or makes use of vocal percussion (such as beatboxing or mouth-made rhythmic sounds) as part of its content or performance.
-
D.
featuresVocalHarmonyBy
Indicates that the subject work includes vocal harmony performances contributed by the specified artist or group.
-
E.
vocalTraining
Indicates that one entity provides or engages in training aimed at improving another entity’s vocal or singing abilities.
- F. None of above.
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_69ef14829fac8190914bef9ecc3005d7 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69fd2cf39b0c8190811b8a6fa9410560 |
completed | May 8, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69fd2ad8dd988190a9899701ba00d917 |
completed | May 8, 2026, 12:14 a.m. |
Created at: April 27, 2026, 8:13 a.m.