Triple
T13225759
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CCIR System B |
E314876
|
entity |
| Predicate | soundModulation |
P23647
|
FINISHED |
| Object | frequency modulation |
—
|
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: frequency modulation | Statement: [CCIR System B, soundModulation, frequency modulation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: soundModulation Context triple: [CCIR System B, soundModulation, frequency modulation]
-
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.
soundMotif
Indicates a recurring or thematically significant sound pattern associated with an entity, event, or context.
-
C.
usesModulation
chosen
Indicates that one entity applies or employs a particular modulation method or scheme in relation to another entity or process.
-
D.
soundAmplification
Indicates that one entity increases the loudness or intensity of another entity’s sound.
-
E.
soundEngine
Indicates that one entity functions as or provides the sound engine (audio processing or synthesis system) used by another entity.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d3128348190836158467e9cfbe2 |
completed | April 10, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69d98bcb21648190aef241de1e7887e2 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:19 p.m.