Triple
T27669570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Semi-Automated Business Research Environment |
E697623
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | real-time data processing system |
C26346
|
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: real-time data processing system Context triple: [Semi-Automated Business Research Environment, instanceOf, real-time data processing system]
-
A.
data processing platform
chosen
A data processing platform is an integrated system that ingests, transforms, analyzes, and manages data at scale to enable efficient, reliable, and repeatable data-driven operations and insights.
-
B.
global data-processing and forecasting system
A global data-processing and forecasting system is an integrated platform that ingests, cleans, analyzes, and models large-scale, heterogeneous data from worldwide sources to generate timely predictions and insights for decision-making.
-
C.
data processing capability
Data processing capability is the capacity of a system to efficiently collect, transform, analyze, and output data to support specific tasks or decision-making processes.
-
D.
real-time data feed
A real-time data feed is a continuous, low-latency stream of updated information delivered as events occur, enabling immediate processing and response.
-
E.
in-memory analytics appliance
An in-memory analytics appliance is a specialized hardware and software system that stores and processes data entirely in RAM to deliver extremely fast, interactive analytical querying and reporting.
- 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_69ef590d458c81909583290c3cd0478b |
completed | April 27, 2026, 12:39 p.m. |
Created at: April 27, 2026, 2:40 p.m.