Triple
T8737037
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Power BI Desktop (Report Server optimized) |
E207411
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | Power BI Desktop edition |
C3280
|
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: Power BI Desktop edition Context triple: [Power BI Desktop (Report Server optimized), instanceOf, Power BI Desktop edition]
-
A.
data visualization platform
chosen
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.
-
B.
on-premises report server
An on-premises report server is a locally hosted system that stores, processes, and delivers business reports within an organization’s own infrastructure, providing secure, controlled access to reporting data and services.
-
C.
database server edition
A database server edition is a specific packaged configuration of database server software that defines its features, performance capabilities, licensing terms, and intended use cases.
-
D.
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.
-
E.
data lake service
A data lake service is a scalable, centralized repository that stores vast amounts of raw, structured, and unstructured data and provides tools for ingestion, management, and analytics.
- 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_69ca835a03a081909d4d4cd01a18c9fb |
completed | March 30, 2026, 2:06 p.m. |
Created at: March 30, 2026, 6:38 p.m.