Triple
T15361512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CIFAR-100 |
E367299
|
entity |
| Predicate | hasTrainingImages |
P118266
|
FINISHED |
| Object | 50000 |
—
|
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: 50000 | Statement: [CIFAR-100, hasTrainingImages, 50000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrainingImages Context triple: [CIFAR-100, hasTrainingImages, 50000]
-
A.
hasTrained
Indicates that one entity has provided training or instruction to another entity.
-
B.
hasTrainingFor
Indicates that an entity has received or possesses training that prepares it for performing a specific task, role, or function.
-
C.
hasTrainingFunction
Indicates that one entity serves as a training function or mechanism for another entity.
-
D.
hasTrainingEnvironment
Indicates that an entity is associated with, or operates within, a specific environment or setting used for training or practice.
-
E.
hasTrainingPipelineFrom
Indicates that something is produced or derived as the result of a specified training pipeline or process.
- 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_69d85a1483788190ad93c2748e8af34b |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e4607408190ab281a7f7a8012d3 |
completed | April 16, 2026, 1:41 a.m. |
| PD | Predicate disambiguation | batch_69deca991e5081908b0df3d1ee7d5338 |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2e413481909d9180a8d78d2c17 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:18 a.m.