Triple
T15217842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Modified National Institute of Standards and Technology database |
E363685
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | machine learning dataset |
C13914
|
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: machine learning dataset Context triple: [Modified National Institute of Standards and Technology database, instanceOf, machine learning dataset]
-
A.
benchmark dataset
A benchmark dataset is a standardized collection of data designed to objectively evaluate, compare, and validate the performance of algorithms, models, or systems on specific tasks.
-
B.
machine learning library
A machine learning library is a collection of tools, algorithms, and interfaces that simplifies building, training, evaluating, and deploying machine learning models.
-
C.
machine learning division
The machine learning division is an organizational unit responsible for researching, developing, and deploying data-driven algorithms and models to solve complex problems and enhance products or services.
-
D.
handwritten digit dataset
chosen
A handwritten digit dataset is a curated collection of images of numerals written by humans, typically labeled with their corresponding digit classes for use in training and evaluating pattern recognition and machine learning models.
-
E.
machine learning book
A machine learning book is a structured, written resource that explains the theories, algorithms, and practical applications of machine learning to help readers understand and apply data-driven modeling techniques.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
Created at: April 10, 2026, 3:11 a.m.