Triple
T29949098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ATI Flipper |
E760720
|
entity |
| Predicate | framebufferConfiguration |
P168285
|
FINISHED |
| Object | 2 MB embedded framebuffer |
—
|
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: 2 MB embedded framebuffer | Statement: [ATI Flipper, framebufferConfiguration, 2 MB embedded framebuffer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: framebufferConfiguration Context triple: [ATI Flipper, framebufferConfiguration, 2 MB embedded framebuffer]
-
A.
canvasConfiguration
Indicates how a canvas or drawing surface is set up, including its layout, properties, and behavior settings.
-
B.
hasFBO
Indicates that one entity has a specified Foreign/Final Beneficial Owner (FBO) associated with it.
-
C.
frameDevice
Indicates that one entity serves as a structural or supporting frame for another device or object.
-
D.
frameGeometry
Indicates that one entity defines or specifies the geometric properties, dimensions, or spatial configuration of another entity’s frame or structural outline.
-
E.
frameWidth
Indicates the measurement of how wide a frame is, typically specifying its horizontal extent or thickness.
- 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_69f2246562b881909d57622f4086d43d |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6780dd5d08190b1ef4e49405a5419 |
completed | May 2, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69f66ec8298c8190b41fe9d182c05676 |
completed | May 2, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69f67256d064819094be04fc1bbbc635 |
completed | May 2, 2026, 9:53 p.m. |
Created at: April 29, 2026, 6:25 p.m.