Triple
T12681982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolby B noise reduction |
E302968
|
entity |
| Predicate | frequencyRangeTargeted |
P1685
|
FINISHED |
| Object | high audio frequencies |
—
|
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: high audio frequencies | Statement: [Dolby B noise reduction, frequencyRangeTargeted, high audio frequencies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frequencyRangeTargeted Context triple: [Dolby B noise reduction, frequencyRangeTargeted, high audio frequencies]
-
A.
frequencyRegion
Indicates that something is associated with, occurs within, or is characterized by a particular range or band of frequencies.
-
B.
frequencyBand
chosen
Indicates the specific range of frequencies within which a signal, measurement, or phenomenon is defined or operates.
-
C.
frequencyCategory
Indicates how often an action, event, or relationship occurs, typically by assigning it to a qualitative frequency level (e.g., rare, occasional, frequent).
-
D.
frequencyDependsOn
Indicates that the frequency of one event, action, or state is determined or influenced by another factor or condition.
-
E.
frequency
Indicates how often an event, action, or relationship occurs within a given period 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961b32dbc81908101fc5f07e26ed3 |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:21 p.m.