Triple
T29858629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GeForce 256 |
E758255
|
entity |
| Predicate | supportsStencilBufferDepth |
P207184
|
FINISHED |
| Object | 8-bit |
—
|
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: 8-bit | Statement: [GeForce 256, supportsStencilBufferDepth, 8-bit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsStencilBufferDepth Context triple: [GeForce 256, supportsStencilBufferDepth, 8-bit]
-
A.
hasDepthRange
Indicates that an entity is associated with a minimum and maximum depth within which it occurs, applies, or is valid.
-
B.
supportsMultisampling
Indicates that an entity provides or enables multisampling functionality, typically for improved rendering quality.
-
C.
supportsAlphaBitDepth
Indicates that one entity is capable of handling or providing image or video data with an alpha (transparency) channel at a specified bit depth.
-
D.
supportsShadingLanguage
Indicates that one entity provides compatibility with, or can correctly interpret and execute, a specified shading language used for programmable graphics rendering.
-
E.
supportsOffscreenRendering
Indicates that the subject is capable of performing rendering operations to an offscreen buffer or surface rather than directly to the visible display.
- 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_69f2245b4dec8190b85f664d918a00a5 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e0f3d88190a4ee7b0673f1ef90 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 29, 2026, 5:47 p.m.