Triple
T36491733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Omniglot |
E899066
|
entity |
| Predicate | numberOfExamplesPerClass |
—
|
GENERATED |
| Object | 20 |
—
|
UNRECOGNIZED GENERATED |
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfExamplesPerClass Context triple: [Omniglot, numberOfExamplesPerClass, 20]
-
A.
originalNumberOfClasses
Indicates the initial total count of classes before any changes such as additions, removals, or merges occur.
-
B.
trainingSetSize
Indicates the number of examples or instances included in a dataset used to train a model or system.
-
C.
numberOfInstances
Indicates the quantity or count of distinct occurrences or instances associated with a given entity or context.
-
D.
hasTrainSplitClassCount
chosen
Indicates the number of instances of a given class that are included in the training split of a dataset.
-
E.
currentNumberOfClasses
Indicates the present count of classes associated with or contained by a given entity.
- 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_69f76e5ad4588190bdbce60c52fbb785 |
completed | May 3, 2026, 3:48 p.m. |
Created at: May 3, 2026, 4:10 p.m.