Triple
T23595002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Golden Buzzer |
E582587
|
entity |
| Predicate | audioEffect |
P152853
|
FINISHED |
| Object | distinctive sound cue |
—
|
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: distinctive sound cue | Statement: [Golden Buzzer, audioEffect, distinctive sound cue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: audioEffect Context triple: [Golden Buzzer, audioEffect, distinctive sound cue]
-
A.
audioModulation
Indicates a relationship where one audio signal or parameter is used to vary or control another audio signal’s characteristics (such as amplitude, frequency, or timbre) over time.
-
B.
audioProcessing
Indicates that one entity performs operations to analyze, modify, or transform audio data associated with another entity.
-
C.
vocalEffects
Indicates that one entity applies or produces specific modifications, enhancements, or stylistic effects on another entity’s vocal sound or performance.
-
D.
soundAmplification
Indicates that one entity increases the loudness or intensity of another entity’s sound.
-
E.
audioStack
Indicates that one audio element is layered or queued on top of another within an ordered audio sequence or mix.
- F. None of above. chosen
Provenance (4 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_69e248f9e0a08190814772847003b1ff |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b08e9aa4819091099dfc2074b22d |
completed | April 29, 2026, 7:17 a.m. |
| PD | Predicate disambiguation | batch_69f118c96a0081908a8ac98ef7e7e60c |
completed | April 28, 2026, 8:30 p.m. |
| PDg | Predicate description generation | batch_69f121cc494081908c987adfcde89b0e |
completed | April 28, 2026, 9:08 p.m. |
Created at: April 17, 2026, 6:42 p.m.