Triple
T12900245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MIT AI Lab software environment |
E308593
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | time-sharing computing environment |
C11152
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: time-sharing computing environment Context triple: [MIT AI Lab software environment, instanceOf, time-sharing computing environment]
-
A.
time-sharing system
chosen
A time-sharing system is an operating system that allows multiple users or processes to share computing resources concurrently by rapidly switching the CPU among them, giving the illusion of simultaneous execution.
-
B.
time-sharing company
A time-sharing company is a business that sells shared ownership or usage rights to a property or resource, allowing multiple clients to use it for specified time periods.
-
C.
multitasking operating system
A multitasking operating system is software that manages computer hardware and resources to run multiple processes or applications seemingly simultaneously by rapidly switching the CPU among them and coordinating their execution.
-
D.
multiuser operating system
A multiuser operating system is a software environment that allows multiple users to access and use a computer system's resources simultaneously and independently, typically through separate user accounts and sessions.
-
E.
computer laboratory
A computer laboratory is a dedicated room or facility equipped with multiple computers and related technologies, providing users with a controlled environment for computing tasks, instruction, and research.
- F. None of above.
Provenance (1 batch)
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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
Created at: April 9, 2026, 5:40 p.m.