Triple
T15361521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CIFAR-100 |
E367299
|
entity |
| Predicate | hasImageResolution |
P33931
|
FINISHED |
| Object | 32x32 pixels |
—
|
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: 32x32 pixels | Statement: [CIFAR-100, hasImageResolution, 32x32 pixels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasImageResolution Context triple: [CIFAR-100, hasImageResolution, 32x32 pixels]
-
A.
hasCameraResolution
Indicates that an entity is associated with a specific camera resolution value or specification.
-
B.
hasResolution
chosen
Indicates that one entity possesses, specifies, or is associated with a particular level or type of resolution (such as detail, clarity, or granularity) in relation to another entity.
-
C.
sensorResolution
Indicates the level of detail or precision with which a sensor can measure or distinguish changes in the observed quantity or environment.
-
D.
supportsDisplayResolution
Indicates that one entity is capable of operating with, rendering, or otherwise accommodating the specified display resolution of another entity.
-
E.
typicalResolution
Indicates the usual or standard level of detail or clarity at which something (such as an image, display, or representation) is normally rendered or presented.
- F. None of above.
Provenance (3 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. |
Created at: April 10, 2026, 3:18 a.m.