Triple
T27888085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Azure Stream Analytics |
E705282
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | complex event processing service |
C53496
|
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: complex event processing service Context triple: [Azure Stream Analytics, instanceOf, complex event processing service]
-
A.
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.
-
B.
event complex
An event complex is a structured grouping of interrelated events that together form a coherent unit of activity, process, or occurrence within a system or domain.
-
C.
composite application platform
A composite application platform is an integrated environment that enables the rapid assembly, orchestration, and management of multiple independent services or components into unified, end-to-end business applications.
-
D.
online analytical processing server
An online analytical processing server is a specialized system that stores, organizes, and processes multidimensional data to support fast, complex analytical queries and business intelligence reporting.
-
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. chosen
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_69ef96b39c448190a9b3aa6672a5168f |
completed | April 27, 2026, 5:02 p.m. |
Created at: April 27, 2026, 6:34 p.m.