NIST Special Database 3
E365304
NIST Special Database 3 is a U.S. National Institute of Standards and Technology collection of handwritten character images that served as a foundational source for later benchmark datasets in pattern recognition and machine learning.
All labels observed (1)
| Label | Occurrences |
|---|---|
| NIST Special Database 3 canonical | 3 |
How this entity was disambiguated
This entity first appeared as the object of triple T3507179 — 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: NIST Special Database 3 Context triple: [MNIST, basedOn, NIST Special Database 3]
-
A.
NIST Special Database 1
NIST Special Database 1 is a U.S. National Institute of Standards and Technology collection of handwritten digit images that served as a primary source for creating the widely used MNIST dataset.
-
B.
Modified National Institute of Standards and Technology database
The Modified National Institute of Standards and Technology database is a large, standardized collection of handwritten digit images widely used for training and evaluating image processing and machine learning algorithms.
-
C.
NISTAR
NISTAR is a radiometer aboard the Deep Space Climate Observatory that measures Earth’s reflected and emitted radiation to study the planet’s energy budget and climate.
-
D.
ISO 10383 MIC database
The ISO 10383 MIC database is an international registry that assigns and maintains standardized Market Identifier Codes (MICs) for securities and derivatives trading venues and related entities worldwide.
-
E.
Integrated Automated Fingerprint Identification System
The Integrated Automated Fingerprint Identification System is the FBI’s large-scale computerized system for storing, searching, and matching fingerprint and biometric data to support criminal identification and investigative work.
- 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: NIST Special Database 3 Target entity description: NIST Special Database 3 is a U.S. National Institute of Standards and Technology collection of handwritten character images that served as a foundational source for later benchmark datasets in pattern recognition and machine learning.
-
A.
NIST Special Database 1
NIST Special Database 1 is a U.S. National Institute of Standards and Technology collection of handwritten digit images that served as a primary source for creating the widely used MNIST dataset.
-
B.
Modified National Institute of Standards and Technology database
The Modified National Institute of Standards and Technology database is a large, standardized collection of handwritten digit images widely used for training and evaluating image processing and machine learning algorithms.
-
C.
NISTAR
NISTAR is a radiometer aboard the Deep Space Climate Observatory that measures Earth’s reflected and emitted radiation to study the planet’s energy budget and climate.
-
D.
ISO 10383 MIC database
The ISO 10383 MIC database is an international registry that assigns and maintains standardized Market Identifier Codes (MICs) for securities and derivatives trading venues and related entities worldwide.
-
E.
Integrated Automated Fingerprint Identification System
The Integrated Automated Fingerprint Identification System is the FBI’s large-scale computerized system for storing, searching, and matching fingerprint and biometric data to support criminal identification and investigative work.
- F. None of above. chosen
Statements (38)
| Predicate | Object |
|---|---|
| instanceOf |
NIST special database
ⓘ
handwritten character image database ⓘ |
| abbreviation |
NIST SD 1
ⓘ
surface form:
NIST SD 3
|
| accessMethod | distribution by NIST ⓘ |
| application |
algorithm evaluation
ⓘ
system benchmarking ⓘ |
| characterType |
alphanumeric characters
ⓘ
handwritten characters ⓘ |
| contains |
handwritten character images
ⓘ
handwritten digits ⓘ handwritten letters ⓘ isolated character images ⓘ |
| countryOfOrigin |
United States of America
ⓘ
surface form:
United States
|
| dataType | image data ⓘ |
| describedAs |
foundational source for later benchmark datasets in machine learning
ⓘ
foundational source for later benchmark datasets in pattern recognition ⓘ |
| documentationPublisher |
NIST technical reports
ⓘ
surface form:
NIST Special Publication series
|
| field |
machine learning
ⓘ
optical character recognition ⓘ pattern recognition ⓘ |
| hasFormat | digital images ⓘ |
| influenced |
MNIST
ⓘ
surface form:
MNIST database
|
| isSubsetOf |
NIST Special Database 19
ⓘ
surface form:
NIST handwriting databases
|
| language | English characters ⓘ |
| license | research use ⓘ |
| maintainedBy | National Institute of Standards and Technology ⓘ |
| organization | U.S. Department of Commerce ⓘ |
| partOf |
NIST Special Database program
ⓘ
surface form:
NIST Special Database series
|
| provider |
National Institute of Standards and Technology
ⓘ
surface form:
NIST Information Technology Laboratory
|
| publisher | National Institute of Standards and Technology ⓘ |
| relatedTo |
NIST Special Database 1
ⓘ
NIST Special Database 19 ⓘ |
| topic |
document analysis
ⓘ
handwriting recognition ⓘ |
| usedFor |
benchmarking machine learning algorithms
ⓘ
benchmarking pattern recognition algorithms ⓘ testing OCR systems ⓘ training OCR systems ⓘ |
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: NIST Special Database 3 Description of subject: NIST Special Database 3 is a U.S. National Institute of Standards and Technology collection of handwritten character images that served as a foundational source for later benchmark datasets in pattern recognition and machine learning.
Referenced by (3)
Full triples — surface form annotated when it differs from this entity's canonical label.
Modified National Institute of Standards and Technology database
→
basedOn
→
NIST Special Database 3
ⓘ