Triple
T7984573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SQL Server Analysis Services Tabular |
E185657
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | tabular data modeling technology |
C15635
|
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: tabular data modeling technology Context triple: [SQL Server Analysis Services Tabular, instanceOf, tabular data modeling technology]
-
A.
data model
A data model is an abstract, structured representation of data and its relationships, designed to organize, define, and constrain how information is stored, accessed, and manipulated within a system.
-
B.
bibliographic data model
A bibliographic data model is a structured framework that defines how information about published and unpublished resources (such as books, articles, and digital media) is represented, organized, and related for purposes of description, discovery, and management.
-
C.
database
A database is an organized collection of structured or unstructured data stored and managed in a way that enables efficient retrieval, modification, and administration.
-
D.
data engineering tool
chosen
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 transformation language
A data transformation language is a specialized programming or query language designed to define, manipulate, and convert data from one structure or format into another.
- 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.