Triple
T8521327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LynxOS |
E201698
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | LynxOS-178 |
E201698
|
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: LynxOS-178 | Statement: [LynxOS, hasVariant, LynxOS-178]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LynxOS-178 Context triple: [LynxOS, hasVariant, LynxOS-178]
-
A.
LynxOS
chosen
LynxOS is a real-time, POSIX-compliant operating system designed for embedded and mission-critical applications, particularly in aerospace, defense, and industrial systems.
-
B.
ARINC 653 (via LynxOS-178 variant)
ARINC 653 (via LynxOS-178 variant) is an avionics software standard that defines time and space partitioning for safety-critical real-time operating systems used in aircraft.
-
C.
VxWorks
VxWorks is a real-time operating system (RTOS) widely used in embedded systems across industries such as aerospace, defense, telecommunications, and industrial automation.
-
D.
OS-9
OS-9 is a real-time, multitasking operating system originally developed by Microware for embedded and industrial computing platforms.
-
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_69ca8321bb44819081b74df0b710276d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe62a490481908ee0ad4ba9a94682 |
completed | March 31, 2026, 3:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce6d3fabb08190a3ad63f9153ad44c |
completed | April 2, 2026, 1:21 p.m. |
Created at: March 30, 2026, 6:16 p.m.