Triple
T29938755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NVIDIA Image Scaling |
E760437
|
entity |
| Predicate | upscalingDomain |
P168279
|
FINISHED |
| Object | spatial domain |
—
|
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: spatial domain | Statement: [NVIDIA Image Scaling, upscalingDomain, spatial domain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: upscalingDomain Context triple: [NVIDIA Image Scaling, upscalingDomain, spatial domain]
-
A.
autoscalingType
Indicates the method or strategy by which a system automatically adjusts its resource capacity (such as scaling up or down) in response to changing demand or conditions.
-
B.
scaleSets
Indicates a relationship where one entity defines or adjusts the size, extent, or magnitude of another entity or set of entities.
-
C.
scalingGranularity
Indicates the level of detail or resolution at which a quantity, process, or system is adjusted or scaled.
-
D.
transportDomain
Indicates a relationship where an entity operates or functions within the domain or context of transportation activities or systems.
-
E.
controlDomain
Indicates that one entity has authority over, manages, or regulates the scope, behavior, or operations of another entity or system.
- F. None of above. chosen
Provenance (4 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_69f22463f3648190a603c3ff305c660b |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f677d7ab2c8190a26f161c559ed05b |
completed | May 2, 2026, 10:16 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 29, 2026, 6:21 p.m.