Triple
T29938768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NVIDIA Freestyle |
E760438
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | post-processing filter system |
C19140
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: post-processing filter system Context triple: [NVIDIA Freestyle, instanceOf, post-processing filter system]
-
A.
filtration
Filtration is the process or mechanism by which a mixture is passed through a medium that selectively allows certain components to pass while retaining others, thereby separating substances based on properties such as size or phase.
-
B.
Alpha processor
An Alpha processor is a high-performance, 64-bit RISC microprocessor architecture designed for fast computation, scalability, and efficient execution of complex instruction workloads.
-
C.
post-production process
chosen
The post-production process is the stage in media creation where recorded material is edited, enhanced, and finalized through tasks such as cutting, sound design, visual effects, color correction, and mastering before distribution.
-
D.
global data-processing and forecasting system
A global data-processing and forecasting system is an integrated platform that ingests, cleans, analyzes, and models large-scale, heterogeneous data from worldwide sources to generate timely predictions and insights for decision-making.
-
E.
analog noise reduction system
An analog noise reduction system is a hardware-based signal processing arrangement that minimizes unwanted noise in analog audio or electronic signals while preserving the integrity of the desired signal.
- F. None of above.
Provenance (1 batch)
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_69f22463f3648190a603c3ff305c660b |
completed | April 29, 2026, 3:31 p.m. |
Created at: April 29, 2026, 6:21 p.m.