Triple
T33173441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amiga 500 Plus |
E849096
|
entity |
| Predicate | bitplanes |
P166320
|
FINISHED |
| Object | up to 6 bitplanes in standard modes |
—
|
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: up to 6 bitplanes in standard modes | Statement: [Amiga 500 Plus, bitplanes, up to 6 bitplanes in standard modes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bitplanes Context triple: [Amiga 500 Plus, bitplanes, up to 6 bitplanes in standard modes]
-
A.
bitplaneCount
chosen
Indicates the number of distinct bitplanes (separate layers of bit-level data) used to represent or encode a value or image.
-
B.
usesBitplanes
Indicates that one entity employs a bitplane-based representation or processing method in relation to another entity or data.
-
C.
extraBitplanesUsedFor
Indicates that additional bitplanes are utilized to provide extra data or capabilities for a specified target (such as an image, layer, or graphical element).
-
D.
bitstream
Indicates a relationship where data is represented or transmitted as a continuous sequence of bits in a defined order.
-
E.
blackAndWhite
Indicates that something is presented or exists in only black and white, without any other colors.
- 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_69f3495be8808190bbf427733df08aad |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6dd3cc0648190a275812d6711275a |
completed | May 3, 2026, 5:29 a.m. |
| PD | Predicate disambiguation | batch_69f6d82eaee081908f06a71546315aea |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:29 a.m.