Triple
T16783361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ARM Mali-G710 MP7 |
E407908
|
entity |
| Predicate | supportsAPI |
P203
|
FINISHED |
| Object | OpenGL ES |
E266145
|
NE 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: OpenGL ES | Statement: [ARM Mali-G710 MP7, supportsAPI, OpenGL ES]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OpenGL ES Context triple: [ARM Mali-G710 MP7, supportsAPI, OpenGL ES]
-
A.
OpenGL ES
chosen
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.
-
B.
OpenGL
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.
-
C.
EGL
EGL is the station code used to identify Eglinton station in transit systems and related services.
-
D.
EGL
EGL is an interface between Khronos rendering APIs like OpenGL ES and the native windowing system, enabling efficient rendering and context management on a variety of platforms.
-
E.
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.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b218d31881908d896e688ebd171c |
completed | April 18, 2026, 4:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00ab056dc88190aeb9e135ae955125 |
completed | May 10, 2026, 3:57 p.m. |
Created at: April 10, 2026, 5:22 a.m.