Triple
T17520956
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GPU |
E426676
|
entity |
| Predicate | supports |
P516
|
FINISHED |
| Object | OpenGL |
—
|
NE NERFINISHED |
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: OpenGL | Statement: [GPU, supports, OpenGL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OpenGL Context triple: [GPU, supports, OpenGL]
-
A.
OpenGL
chosen
OpenGL is a cross-language, cross-platform application programming interface (API) for rendering 2D and 3D vector graphics, widely used in games, simulations, and professional visualization.
-
B.
OpenGL ES
OpenGL ES is a cross-platform, royalty-free 2D and 3D graphics API designed for embedded systems such as mobile devices, game consoles, and automotive displays.
-
C.
OGL
OGL is the IATA airport code for Eugene F. Correia International Airport, a regional airport serving Georgetown, Guyana.
-
D.
OpenGL SC
OpenGL SC is a safety-critical profile of the OpenGL graphics API designed for use in high-reliability, real-time, and embedded systems such as avionics and automotive applications.
-
E.
Glew
Glew is a town in the southern Greater Buenos Aires area of Argentina that serves as a stop on the Roca Line suburban railway network.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889de677081909b22d2657b1f0292 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452d23cf08190925510344fa36f57 |
completed | April 19, 2026, 3:58 a.m. |
Created at: April 10, 2026, 5:49 a.m.