DLSS (Deep Learning Super Sampling)
E41923
DLSS (Deep Learning Super Sampling) is an NVIDIA graphics technology that uses deep learning to upscale lower-resolution images in real time, improving performance and visual quality in video games.
All labels observed (14)
| Label | Occurrences |
|---|---|
| NVIDIA DLSS | 7 |
| DLSS | 2 |
| DLSS 3 | 2 |
| DLSS (Deep Learning Super Sampling) canonical | 1 |
| DLSS 1.0 | 1 |
| DLSS 2.0 | 1 |
| DLSS 2.1 | 1 |
| DLSS 2.2 | 1 |
| DLSS 3.5 | 1 |
| DLSS Frame Generation | 1 |
| Deep Learning Super Sampling | 1 |
| NVIDIA Deep Learning Super Sampling | 1 |
| Nvidia DLSS | 1 |
| RTX Video Super Resolution | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T328458 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DLSS (Deep Learning Super Sampling) Context triple: [NVIDIA Corporation, notableTechnology, DLSS (Deep Learning Super Sampling)]
-
A.
RTX
RTX is a major American aerospace and defense company formed from the merger of Raytheon Company and United Technologies Corporation, known for its advanced military, aviation, and cybersecurity technologies.
-
B.
Intel Arc
Intel Arc is a line of discrete graphics processing units (GPUs) developed by Intel for gaming, content creation, and high-performance graphics workloads.
-
C.
DirectX
DirectX is a collection of application programming interfaces (APIs) developed by Microsoft that enables high-performance handling of graphics, sound, and other multimedia tasks, especially for games, on Windows platforms.
-
D.
Element AI
Element AI was a Montreal-based artificial intelligence company and research lab known for developing enterprise AI solutions and advancing deep learning research.
-
E.
DALL·E
DALL·E is an AI model developed by OpenAI that generates images from natural language descriptions, enabling text-to-image synthesis.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DLSS (Deep Learning Super Sampling) Target entity description: DLSS (Deep Learning Super Sampling) is an NVIDIA graphics technology that uses deep learning to upscale lower-resolution images in real time, improving performance and visual quality in video games.
-
A.
RTX
RTX is a major American aerospace and defense company formed from the merger of Raytheon Company and United Technologies Corporation, known for its advanced military, aviation, and cybersecurity technologies.
-
B.
Intel Arc
Intel Arc is a line of discrete graphics processing units (GPUs) developed by Intel for gaming, content creation, and high-performance graphics workloads.
-
C.
DirectX
DirectX is a collection of application programming interfaces (APIs) developed by Microsoft that enables high-performance handling of graphics, sound, and other multimedia tasks, especially for games, on Windows platforms.
-
D.
Element AI
Element AI was a Montreal-based artificial intelligence company and research lab known for developing enterprise AI solutions and advancing deep learning research.
-
E.
DALL·E
DALL·E is an AI model developed by OpenAI that generates images from natural language descriptions, enabling text-to-image synthesis.
- F. None of above. chosen
Statements (51)
| Predicate | Object |
|---|---|
| instanceOf |
deep learning-based graphics technology
ⓘ
image upscaling technology ⓘ real-time rendering technology ⓘ |
| appliesTo |
real-time 3D rendering
ⓘ
video games ⓘ |
| competesWith |
AMD FidelityFX Super Resolution
ⓘ
Intel XeSS ⓘ
linked to:
XeSS
|
| componentOf |
NVIDIA RTX technologies
ⓘ
linked to:
RTX
|
| developer |
NVIDIA
ⓘ
linked to:
NVIDIA Corporation
|
| fullName |
Deep Learning Super Sampling
ⓘ
linked to:
DLSS (Deep Learning Super Sampling)
|
| hardwareRequirement |
NVIDIA GPU with Tensor Cores
ⓘ
linked to:
NVIDIA Tesla data center GPUs
NVIDIA RTX graphics card ⓘ |
| improves |
4K gaming performance
ⓘ
ray-traced game performance ⓘ |
| initialReleaseDate | 2018 ⓘ |
| introducedBy |
NVIDIA Turing architecture
ⓘ
linked to:
RTX
|
| keyBenefit |
better performance at high resolutions
ⓘ
higher frame rates ⓘ improved image sharpness ⓘ |
| manufacturer |
NVIDIA
ⓘ
linked to:
NVIDIA Corporation
|
| operatesOn | lower-resolution input images ⓘ |
| primaryPurpose |
improve gaming performance
ⓘ
improve visual quality ⓘ real-time image upscaling ⓘ |
| produces | higher-resolution output images ⓘ |
| qualityMode |
Balanced
ⓘ
Performance ⓘ Quality ⓘ Ultra Performance ⓘ |
| relatedTo |
NVIDIA Image Scaling
ⓘ
NVIDIA Ray Tracing ⓘ NVIDIA Reflex ⓘ |
| requires |
NVIDIA driver support
ⓘ
game integration ⓘ |
| supports | multiple quality modes ⓘ |
| targetPlatform |
Windows PC
ⓘ
cloud gaming services ⓘ some game consoles with NVIDIA GPUs ⓘ |
| uses |
generalized AI model (DLSS 2.x and later)
ⓘ
motion vectors ⓘ per-game trained AI models (DLSS 1.0) ⓘ temporal accumulation ⓘ |
| usesTechnology |
AI upscaling
ⓘ
deep learning ⓘ neural networks ⓘ |
| version |
DLSS 1.0
ⓘ
linked to:
DLSS (Deep Learning Super Sampling)
DLSS 2.0 ⓘ
linked to:
DLSS (Deep Learning Super Sampling)
DLSS 2.1 ⓘ
linked to:
DLSS (Deep Learning Super Sampling)
DLSS 2.2 ⓘ
linked to:
DLSS (Deep Learning Super Sampling)
DLSS 3 ⓘ
linked to:
DLSS (Deep Learning Super Sampling)
DLSS 3.5 ⓘ
linked to:
DLSS (Deep Learning Super Sampling)
|
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: DLSS (Deep Learning Super Sampling) Description of subject: DLSS (Deep Learning Super Sampling) is an NVIDIA graphics technology that uses deep learning to upscale lower-resolution images in real time, improving performance and visual quality in video games.
Referenced by (22)
Full triples — surface form annotated when it differs from this entity's canonical label.
subject linked to:
DLSS (Deep Learning Super Sampling)
linked to: DLSS (Deep Learning Super Sampling)
subject linked to:
DLSS (Deep Learning Super Sampling)
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subject linked to:
DLSS (Deep Learning Super Sampling)
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subject linked to:
DLSS (Deep Learning Super Sampling)
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subject linked to:
DLSS (Deep Learning Super Sampling)
linked to: DLSS (Deep Learning Super Sampling)
subject linked to:
DLSS (Deep Learning Super Sampling)
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subject linked to:
DLSS (Deep Learning Super Sampling)
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linked to: DLSS (Deep Learning Super Sampling)
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linked to: DLSS (Deep Learning Super Sampling)
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linked to: DLSS (Deep Learning Super Sampling)