Triple
T27046877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Playlist For An Extreme Occasion |
E684659
|
entity |
| Predicate | audioDynamics |
P51622
|
FINISHED |
| Object | loud |
—
|
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: loud | Statement: [Playlist For An Extreme Occasion, audioDynamics, loud]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: audioDynamics Context triple: [Playlist For An Extreme Occasion, audioDynamics, loud]
-
A.
audioEffect
Indicates that one entity applies or represents an audio processing effect that modifies the sound characteristics of another entity.
-
B.
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.
-
C.
audioStack
Indicates that one audio element is layered or queued on top of another within an ordered audio sequence or mix.
-
D.
soundAmplification
Indicates that one entity increases the loudness or intensity of another entity’s sound.
-
E.
hasDynamics
chosen
Indicates that one entity exhibits or is characterized by specific dynamic behavior, changes, or variations over time in relation to another entity or context.
- 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_69ef148193c48190bb1a0cfae6a407c4 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f622acea248190a90c685058f42184 |
completed | May 2, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69f61b3ee7b08190a0a1bc5d26b757aa |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 8:11 a.m.