Triple
T7984721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Power BI Service dataflows |
E185660
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | cloud-based data preparation feature |
C11843
|
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: cloud-based data preparation feature Context triple: [Power BI Service dataflows, instanceOf, cloud-based data preparation feature]
-
A.
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.
-
B.
data engineering tool
A data engineering tool is a software solution that enables the collection, transformation, orchestration, and management of data pipelines to ensure reliable, scalable, and efficient data processing.
-
C.
managed data ingestion service
A managed data ingestion service is a fully hosted platform that reliably collects, transforms, and routes data from diverse sources into target systems at scale, handling infrastructure, scaling, and monitoring automatically.
-
D.
data integration platform
chosen
A data integration platform is a system that connects, transforms, and consolidates data from disparate sources into a unified, accessible, and consistent view for analysis and operational use.
-
E.
data visualization platform
A data visualization platform is a software system that enables users to transform raw data into interactive, graphical representations to explore insights, identify patterns, and communicate information effectively.
- 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_69ca829a2cfc819083d591d58ec04075 |
completed | March 30, 2026, 2:03 p.m. |
Created at: March 30, 2026, 5:15 p.m.