Triple
T15218070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fashion-MNIST |
E363689
|
entity |
| Predicate | typicalSplit |
P117564
|
FINISHED |
| Object | 60000 train / 10000 test |
—
|
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: 60000 train / 10000 test | Statement: [Fashion-MNIST, typicalSplit, 60000 train / 10000 test]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSplit Context triple: [Fashion-MNIST, typicalSplit, 60000 train / 10000 test]
-
A.
typicalIn
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
B.
typicalSegmentType
Indicates that something is classified as belonging to a usual or characteristic type of segment within a broader structure or sequence.
-
C.
typicalBase
Indicates that one entity serves as the standard or most representative base or foundation for another entity in typical or common cases.
-
D.
typicalSection
Indicates that one section is a standard, representative, or commonly occurring instance within a broader set or structure of sections.
-
E.
dividedBetween
Indicates that something is partitioned or shared among two or more distinct entities or groups.
- 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_69d85a0ce24c81909c4d3b6475548c95 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0076f90c481909989befe031a2cae |
completed | April 15, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69deca8479188190b2e5d3bc708d7d07 |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2ca6148190967c319728ec3661 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:11 a.m.