Triple
T29100342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Extra Half-Brite |
E736622
|
entity |
| Predicate | memoryCostComparedTo32Color |
P171014
|
FINISHED |
| Object | requires one additional bitplane |
—
|
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: requires one additional bitplane | Statement: [Extra Half-Brite, memoryCostComparedTo32Color, requires one additional bitplane]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memoryCostComparedTo32Color Context triple: [Extra Half-Brite, memoryCostComparedTo32Color, requires one additional bitplane]
-
A.
colorDepth
Indicates the bit-depth used to represent the color information of an image or display, defining how many distinct colors can be shown.
-
B.
hasLowerCostPerBitThan
Indicates that the cost required to transmit or store each unit of data (bit) for one entity is lower than that for another entity.
-
C.
bitplaneCount
Indicates the number of distinct bitplanes (separate layers of bit-level data) used to represent or encode a value or image.
-
D.
maxColorsOnScreen
Indicates the maximum number of distinct colors that can be displayed on the screen at the same time.
-
E.
hasNumberOfColors
Indicates the quantity of distinct colors associated with an 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_69f077ec765c81909474c88bcc8bab43 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f6984bb55c8190862eb8796868d188 |
completed | May 3, 2026, 12:35 a.m. |
| PD | Predicate disambiguation | batch_69f69661e6ec8190948251c7516a32ad |
completed | May 3, 2026, 12:27 a.m. |
| PDg | Predicate description generation | batch_69f6978ec27c8190a488e1f9c2566d38 |
completed | May 3, 2026, 12:32 a.m. |
Created at: April 28, 2026, 11:11 a.m.