Triple
T17499215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SPICE in-memory engine |
E426149
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | Amazon QuickSight component |
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: Amazon QuickSight component Context triple: [SPICE in-memory engine, instanceOf, Amazon QuickSight component]
-
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.
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.
-
C.
analytics platform
An analytics platform is a software system that collects, processes, and visualizes data from various sources to provide insights and support data-driven decision-making.
-
D.
collaborative data science platform
A collaborative data science platform is an integrated environment where multiple users can jointly develop, run, and share data workflows, analyses, and models using shared datasets, tools, and computational resources.
-
E.
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.
- 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
Created at: April 10, 2026, 5:48 a.m.