Triple
T18204604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ViT |
E435871
|
entity |
| Predicate | patchSizeTypical |
P67473
|
FINISHED |
| Object | 16x16 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: 16x16 pixels | Statement: [ViT, patchSizeTypical, 16x16 pixels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: patchSizeTypical Context triple: [ViT, patchSizeTypical, 16x16 pixels]
-
A.
typicalUnitSize
Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
-
B.
peakSize
Indicates the magnitude or height of a peak within a given signal, distribution, or dataset.
-
C.
typicalPanelSize
Indicates the usual or standard dimensions associated with a given panel.
-
D.
typicalWidth
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
-
E.
typicalDimension
chosen
Indicates that one entity represents a standard or characteristic measurement (such as size, length, or capacity) typically associated with another entity.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e222831081908f7d5500424e3acb |
completed | April 19, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:32 a.m.