Triple
T21832324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MOS Technology VIC-II |
E539027
|
entity |
| Predicate | bitmapModeResolution |
P79780
|
FINISHED |
| Object | 320×200 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: 320×200 pixels | Statement: [MOS Technology VIC-II, bitmapModeResolution, 320×200 pixels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bitmapModeResolution Context triple: [MOS Technology VIC-II, bitmapModeResolution, 320×200 pixels]
-
A.
printingResolution
Indicates the level of detail or clarity at which something is printed, typically measured as resolution (e.g., dots per inch).
-
B.
samplingResolution
Indicates the level of detail or granularity at which data is sampled or measurements are taken in a process or system.
-
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.
pixelScale
Indicates the ratio or conversion factor between pixel units and real-world or coordinate-space units in a representation or image.
-
E.
targetResolution
chosen
Indicates the specific resolution or level of detail that an action, process, or system is intended to achieve or operate at.
- 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_69e0c475cda88190987d08f23caebdc1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0a7a4d2d0819088ded045caeab52d |
completed | April 28, 2026, 12:27 p.m. |
| PD | Predicate disambiguation | batch_69e6be8c14748190bdcc44a14d50bea4 |
completed | April 21, 2026, 12:02 a.m. |
Created at: April 16, 2026, 6:55 p.m.