Triple
T29938817
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FSR |
E760439
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | spatial upscaling technology |
C9940
|
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: spatial upscaling technology Context triple: [FSR, instanceOf, spatial upscaling technology]
-
A.
image upscaling technology
chosen
Image upscaling technology is a set of algorithms and tools that increase the resolution and apparent quality of digital images by intelligently adding or refining pixel data, often using advanced methods like machine learning or deep learning.
-
B.
remote sensing technique
A remote sensing technique is a method for acquiring information about objects or areas from a distance, typically using satellite or airborne sensors that detect and measure reflected or emitted electromagnetic radiation.
-
C.
spatial computing platform
A spatial computing platform is an integrated hardware and software environment that blends digital content with the physical world, enabling users to interact with 3D information and experiences in real space.
-
D.
spatial planning instrument
A spatial planning instrument is a formal tool, policy, or regulatory mechanism used by authorities to guide, control, and coordinate the use and development of land and space within a defined territory.
-
E.
static spacetime
A static spacetime is a spacetime that admits a global timelike Killing vector field that is hypersurface-orthogonal, so its geometry is time-independent and free of rotation.
- 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.