Triple
T5100740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | audioOS |
E114974
|
entity |
| Predicate | kernelType |
P5103
|
FINISHED |
| Object | XNU |
E41424
|
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: XNU | Statement: [audioOS, kernelType, XNU]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: XNU Context triple: [audioOS, kernelType, XNU]
-
A.
XNU
chosen
XNU is the hybrid operating system kernel developed by Apple that powers macOS and other Apple platforms, combining components from Mach and BSD.
-
B.
I/O Kit
I/O Kit is macOS and iOS’s object-oriented driver framework that manages hardware devices and their interaction with the operating system.
-
C.
Mach microkernel
Mach microkernel is a pioneering microkernel-based operating system kernel developed at Carnegie Mellon University, known for its message-passing architecture and influence on systems like NeXTSTEP and early versions of macOS.
-
D.
NeXTSTEP
NeXTSTEP was an advanced Unix-based operating system and development environment created by NeXT Inc., notable for its object-oriented frameworks and influential role in the later development of macOS and iOS.
-
E.
QNX
QNX is a commercial, real-time, microkernel-based operating system widely used in embedded and safety-critical applications such as automotive, industrial, and medical systems.
- 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_69bd443fc49c819089629c00e311310c |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd758381dc8190ac491788d27ab8e0 |
completed | March 20, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beba8977f481908b0d55a9cd28d492 |
completed | March 21, 2026, 3:34 p.m. |
Created at: March 20, 2026, 1:40 p.m.