Triple
T3740555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | System M |
E79686
|
entity |
| Predicate | audioModulationType |
P17349
|
FINISHED |
| Object | frequency modulation (FM) |
—
|
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 (FM) | Statement: [System M, audioModulationType, frequency modulation (FM)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: audioModulationType Context triple: [System M, audioModulationType, frequency modulation (FM)]
-
A.
audioModulation
chosen
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.
usesModulation
Indicates that one entity applies or employs a particular modulation method or scheme in relation to another entity or process.
-
C.
videoModulation
Indicates a relationship where one entity alters or controls the characteristics of a video signal or stream, such as its amplitude, frequency, or encoding parameters.
-
D.
audioChip
Indicates that one entity functions as, or contains, an audio processing chip in relation to another entity.
-
E.
tuningMethod
Indicates the method or approach used to adjust or optimize something’s parameters or performance.
- 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_69ad8b115610819095b02007da5ca3cb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb5344fc8190b183aca5c04e3bcc |
completed | March 8, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69adc048f28c819092bed16a95a3cac1 |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:34 p.m.