Triple
T34100958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GOMS model of human–computer interaction |
E874567
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | predictive user performance model |
C58732
|
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: predictive user performance model Context triple: [GOMS model of human–computer interaction, instanceOf, predictive user performance model]
-
A.
performance model
A performance model is an abstract representation that predicts or explains how a system, process, or individual will behave and perform under specified conditions using quantitative or qualitative metrics.
-
B.
idealized prediction method
An idealized prediction method is a theoretical procedure that, given complete and accurate information about a system and its governing rules, produces perfectly accurate forecasts of future states or outcomes.
-
C.
formal theory of universal prediction
A formal theory of universal prediction is a mathematical framework that defines and analyzes predictors capable of making optimal or near-optimal forecasts across all computable environments, typically using concepts like algorithmic probability and Kolmogorov complexity.
-
D.
GOMS family model
chosen
The GOMS family model is a set of cognitive modeling techniques that describe and predict user interaction with systems by decomposing tasks into goals, operators, methods, and selection rules.
-
E.
public services performance study
A public services performance study systematically evaluates the efficiency, effectiveness, equity, and quality of government or publicly funded services to inform improvements in policy and practice.
- 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_69f349a735208190a1dbfb1c2a121059 |
completed | April 30, 2026, 12:23 p.m. |
Created at: May 1, 2026, 1:53 a.m.