Triple
T8472879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VDP (Video Display Processor) |
E200318
|
entity |
| Predicate | maxSpritesOnScreen |
P82805
|
FINISHED |
| Object | 80 sprites |
—
|
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: 80 sprites | Statement: [VDP (Video Display Processor), maxSpritesOnScreen, 80 sprites]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maxSpritesOnScreen Context triple: [VDP (Video Display Processor), maxSpritesOnScreen, 80 sprites]
-
A.
maxColorsOnScreen
Indicates the maximum number of distinct colors that can be displayed on the screen at the same time.
-
B.
maximumSlotsRecommended
Indicates the highest number of slots that is advised or suggested to be used in a given context.
-
C.
numberOfStills
Indicates the quantity of still images associated with or contained in a given entity or context.
-
D.
displayCount
Indicates the number of times something is shown or presented, typically within a given context or interface.
-
E.
hasNumberOfScreens
Indicates the quantity of screens associated with or contained in a given entity.
- 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_69ca831a4f348190bfdd09250e86ae35 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe4f4fbf481909e4fd7c078b27477 |
completed | March 31, 2026, 3:15 p.m. |
| PD | Predicate disambiguation | batch_69cbd104250c8190b4c499dcc9937494 |
completed | March 31, 2026, 1:49 p.m. |
| PDg | Predicate description generation | batch_69cbe12dd0b88190a38ec4d15dcc870b |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 6:11 p.m.